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An autonomous multi-turn tool-calling agentic base model for RL agent training | 1 | [removed] | 2025-06-10T07:47:35 | https://huggingface.co/eliuakk/mirau-agent-14b-base | EliaukMouse | huggingface.co | 1970-01-01T00:00:00 | 0 | {} | 1l7svmk | false | null | t3_1l7svmk | /r/LocalLLaMA/comments/1l7svmk/an_autonomous_multiturn_toolcalling_agentic_base/ | false | false | 1 | {'enabled': False, 'images': [{'id': 'AKaMSOfJYnlG078czfFbfWqAb0eBPGDcHKrAXmnU50U', 'resolutions': [{'height': 58, 'url': 'https://external-preview.redd.it/dNdqJyhtXwj87G8KuNit74iQ4LPkok_1Pa60DPDQATc.jpg?width=108&crop=smart&auto=webp&s=e9e90a25625ad3f9171819c90d87173ce47b20aa', 'width': 108}, {'height': 116, 'url': 'https://external-preview.redd.it/dNdqJyhtXwj87G8KuNit74iQ4LPkok_1Pa60DPDQATc.jpg?width=216&crop=smart&auto=webp&s=113d5a22c282559523f7071bd18f075a1adeb4fe', 'width': 216}, {'height': 172, 'url': 'https://external-preview.redd.it/dNdqJyhtXwj87G8KuNit74iQ4LPkok_1Pa60DPDQATc.jpg?width=320&crop=smart&auto=webp&s=ca0236d18c5925fed7b96bf162c169d2f4631e11', 'width': 320}, {'height': 345, 'url': 'https://external-preview.redd.it/dNdqJyhtXwj87G8KuNit74iQ4LPkok_1Pa60DPDQATc.jpg?width=640&crop=smart&auto=webp&s=f843f791022421e80147e86ad1a24e06209b5cd8', 'width': 640}, {'height': 518, 'url': 'https://external-preview.redd.it/dNdqJyhtXwj87G8KuNit74iQ4LPkok_1Pa60DPDQATc.jpg?width=960&crop=smart&auto=webp&s=9cea9d6b43507fab2619a1dbe1414da6bda156de', 'width': 960}, {'height': 583, 'url': 'https://external-preview.redd.it/dNdqJyhtXwj87G8KuNit74iQ4LPkok_1Pa60DPDQATc.jpg?width=1080&crop=smart&auto=webp&s=cc2d248c7d109c6e62b2de9fe7b74127bb26a91b', 'width': 1080}], 'source': {'height': 648, 'url': 'https://external-preview.redd.it/dNdqJyhtXwj87G8KuNit74iQ4LPkok_1Pa60DPDQATc.jpg?auto=webp&s=8b4c2d15714bbf7cf2f67fabe38467149a7fb69c', 'width': 1200}, 'variants': {}}]} |
|
What level can we expect a Deepseek R2 rollout to clash with? | 0 | Is a Opus 4/ ChatGPT o4 level on writing/creativity/problem solving/coding possible? I cannot imagine how large R2 would need to match them in those fields | 2025-06-10T07:50:53 | https://www.reddit.com/r/LocalLLaMA/comments/1l7sxe4/what_level_can_we_expect_a_deepseek_r2_rollout_to/ | Caffdy | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1l7sxe4 | false | null | t3_1l7sxe4 | /r/LocalLLaMA/comments/1l7sxe4/what_level_can_we_expect_a_deepseek_r2_rollout_to/ | false | false | self | 0 | null |
Updates to Apple's On-Device and Server Foundation Language Models | 1 | 2025-06-10T07:52:22 | https://machinelearning.apple.com/research/apple-foundation-models-2025-updates | cpldcpu | machinelearning.apple.com | 1970-01-01T00:00:00 | 0 | {} | 1l7sy6m | false | null | t3_1l7sy6m | /r/LocalLLaMA/comments/1l7sy6m/updates_to_apples_ondevice_and_server_foundation/ | false | false | 1 | {'enabled': False, 'images': [{'id': 'i1zWCudooEbEVKZGX6lWeQZBaUZDb_YHWhzbbT8hnsU', 'resolutions': [{'height': 56, 'url': 'https://external-preview.redd.it/xwvAu1ztoOvOhx7n2EoT8sRix4FTcRO810CrbO3VhbM.jpg?width=108&crop=smart&auto=webp&s=d20f4791540ae8ac6bd7a69f1ee155c329c6ddd3', 'width': 108}, {'height': 113, 'url': 'https://external-preview.redd.it/xwvAu1ztoOvOhx7n2EoT8sRix4FTcRO810CrbO3VhbM.jpg?width=216&crop=smart&auto=webp&s=15915a53d5c38ca7377c6cafc9c4d2bf31d370f2', 'width': 216}, {'height': 168, 'url': 'https://external-preview.redd.it/xwvAu1ztoOvOhx7n2EoT8sRix4FTcRO810CrbO3VhbM.jpg?width=320&crop=smart&auto=webp&s=d1e340bd0a5ffaed4d7903eb6fd54f6b819a1f19', 'width': 320}, {'height': 336, 'url': 'https://external-preview.redd.it/xwvAu1ztoOvOhx7n2EoT8sRix4FTcRO810CrbO3VhbM.jpg?width=640&crop=smart&auto=webp&s=40e5ffcb35a4ce46e023c171c46660884aebba49', 'width': 640}, {'height': 504, 'url': 'https://external-preview.redd.it/xwvAu1ztoOvOhx7n2EoT8sRix4FTcRO810CrbO3VhbM.jpg?width=960&crop=smart&auto=webp&s=f4edc5ef480352298f79f4cc19c8b0173813d28c', 'width': 960}, {'height': 567, 'url': 'https://external-preview.redd.it/xwvAu1ztoOvOhx7n2EoT8sRix4FTcRO810CrbO3VhbM.jpg?width=1080&crop=smart&auto=webp&s=ca387a9864c2800b307d6cfcc993afd8d0d6f0df', 'width': 1080}], 'source': {'height': 630, 'url': 'https://external-preview.redd.it/xwvAu1ztoOvOhx7n2EoT8sRix4FTcRO810CrbO3VhbM.jpg?auto=webp&s=e32ed632169ab6ba70cb03567bd87b9a69fc1ad5', 'width': 1200}, 'variants': {}}]} |
||
Apple is using a "Parallel-Track" MoE architecture in their edge models. Background information. | 168 | 2025-06-10T07:53:57 | https://machinelearning.apple.com/research/apple-foundation-models-2025-updates | cpldcpu | machinelearning.apple.com | 1970-01-01T00:00:00 | 0 | {} | 1l7sz1l | false | null | t3_1l7sz1l | /r/LocalLLaMA/comments/1l7sz1l/apple_is_using_a_paralleltrack_moe_architecture/ | false | false | 168 | {'enabled': False, 'images': [{'id': 'i1zWCudooEbEVKZGX6lWeQZBaUZDb_YHWhzbbT8hnsU', 'resolutions': [{'height': 56, 'url': 'https://external-preview.redd.it/xwvAu1ztoOvOhx7n2EoT8sRix4FTcRO810CrbO3VhbM.jpg?width=108&crop=smart&auto=webp&s=d20f4791540ae8ac6bd7a69f1ee155c329c6ddd3', 'width': 108}, {'height': 113, 'url': 'https://external-preview.redd.it/xwvAu1ztoOvOhx7n2EoT8sRix4FTcRO810CrbO3VhbM.jpg?width=216&crop=smart&auto=webp&s=15915a53d5c38ca7377c6cafc9c4d2bf31d370f2', 'width': 216}, {'height': 168, 'url': 'https://external-preview.redd.it/xwvAu1ztoOvOhx7n2EoT8sRix4FTcRO810CrbO3VhbM.jpg?width=320&crop=smart&auto=webp&s=d1e340bd0a5ffaed4d7903eb6fd54f6b819a1f19', 'width': 320}, {'height': 336, 'url': 'https://external-preview.redd.it/xwvAu1ztoOvOhx7n2EoT8sRix4FTcRO810CrbO3VhbM.jpg?width=640&crop=smart&auto=webp&s=40e5ffcb35a4ce46e023c171c46660884aebba49', 'width': 640}, {'height': 504, 'url': 'https://external-preview.redd.it/xwvAu1ztoOvOhx7n2EoT8sRix4FTcRO810CrbO3VhbM.jpg?width=960&crop=smart&auto=webp&s=f4edc5ef480352298f79f4cc19c8b0173813d28c', 'width': 960}, {'height': 567, 'url': 'https://external-preview.redd.it/xwvAu1ztoOvOhx7n2EoT8sRix4FTcRO810CrbO3VhbM.jpg?width=1080&crop=smart&auto=webp&s=ca387a9864c2800b307d6cfcc993afd8d0d6f0df', 'width': 1080}], 'source': {'height': 630, 'url': 'https://external-preview.redd.it/xwvAu1ztoOvOhx7n2EoT8sRix4FTcRO810CrbO3VhbM.jpg?auto=webp&s=e32ed632169ab6ba70cb03567bd87b9a69fc1ad5', 'width': 1200}, 'variants': {}}]} |
||
Ragbits PDF document ingestion | 1 | [removed] | 2025-06-10T07:59:26 | https://www.reddit.com/r/LocalLLaMA/comments/1l7t1uu/ragbits_pdf_document_ingestion/ | TheOneInfiniteC | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1l7t1uu | false | null | t3_1l7t1uu | /r/LocalLLaMA/comments/1l7t1uu/ragbits_pdf_document_ingestion/ | false | false | self | 1 | null |
Lmarena censorship! They won't let me translate an article from Le Monde! | 1 | [removed] | 2025-06-10T09:02:58 | https://www.reddit.com/r/LocalLLaMA/comments/1l7tynb/lmarena_censorship_they_wont_let_me_translate_an/ | Salty-Garage7777 | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1l7tynb | false | null | t3_1l7tynb | /r/LocalLLaMA/comments/1l7tynb/lmarena_censorship_they_wont_let_me_translate_an/ | false | false | self | 1 | {'enabled': False, 'images': [{'id': 'GYmsOdqaFPUGR-rEQiO1gnUjZfkHVHj01hMCYIQYWy8', 'resolutions': [{'height': 72, 'url': 'https://external-preview.redd.it/XO9iaLwFXasTgVLBRdr22ua642k1mWcP7F4qpJkiEkY.jpg?width=108&crop=smart&auto=webp&s=56bf7e61db5013dc8238ed949803b3232c4cccb6', 'width': 108}, {'height': 144, 'url': 'https://external-preview.redd.it/XO9iaLwFXasTgVLBRdr22ua642k1mWcP7F4qpJkiEkY.jpg?width=216&crop=smart&auto=webp&s=f7535f0035c9fbb614434c4e1e85e4f8a2325641', 'width': 216}, {'height': 213, 'url': 'https://external-preview.redd.it/XO9iaLwFXasTgVLBRdr22ua642k1mWcP7F4qpJkiEkY.jpg?width=320&crop=smart&auto=webp&s=5627868e4d0d1d8f90576e0d0a86af4cfe3241f8', 'width': 320}, {'height': 426, 'url': 'https://external-preview.redd.it/XO9iaLwFXasTgVLBRdr22ua642k1mWcP7F4qpJkiEkY.jpg?width=640&crop=smart&auto=webp&s=f754cc8b6a91132ac4580270d97247dbae376869', 'width': 640}, {'height': 640, 'url': 'https://external-preview.redd.it/XO9iaLwFXasTgVLBRdr22ua642k1mWcP7F4qpJkiEkY.jpg?width=960&crop=smart&auto=webp&s=d3c3b72ad83124835ae0a66ba17bb6a7f979b097', 'width': 960}, {'height': 720, 'url': 'https://external-preview.redd.it/XO9iaLwFXasTgVLBRdr22ua642k1mWcP7F4qpJkiEkY.jpg?width=1080&crop=smart&auto=webp&s=f27c5696a2fa763a399db93e09937c4efcf95477', 'width': 1080}], 'source': {'height': 960, 'url': 'https://external-preview.redd.it/XO9iaLwFXasTgVLBRdr22ua642k1mWcP7F4qpJkiEkY.jpg?auto=webp&s=cfef3bb699ea217508b15a2397b675fdd7c5f927', 'width': 1440}, 'variants': {}}]} |
A link to a post that was blocked in this group | 1 | [removed] | 2025-06-10T09:08:41 | https://www.reddit.com/r/LocalLLaMA/comments/1l7u1nn/a_link_to_a_post_that_was_blocked_in_this_group/ | Salty-Garage7777 | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1l7u1nn | false | null | t3_1l7u1nn | /r/LocalLLaMA/comments/1l7u1nn/a_link_to_a_post_that_was_blocked_in_this_group/ | false | false | self | 1 | null |
Free local AI robotics hackathon this week. Come build some open source AI robots. | 2 | [removed] | 2025-06-10T09:11:15 | Zealousideal-Cut590 | i.redd.it | 1970-01-01T00:00:00 | 0 | {} | 1l7u310 | false | null | t3_1l7u310 | /r/LocalLLaMA/comments/1l7u310/free_local_ai_robotics_hackathon_this_week_come/ | false | false | 2 | {'enabled': True, 'images': [{'id': 'j79xVvH9Lo1Dx3TeIKc5olsiYSyt7Zvtv7LI6nIuHzo', 'resolutions': [{'height': 108, 'url': 'https://preview.redd.it/0npcuf7hg26f1.png?width=108&crop=smart&auto=webp&s=d19e6b37a8320cfe4ae63cfe2d1402983ca3c0da', 'width': 108}, {'height': 216, 'url': 'https://preview.redd.it/0npcuf7hg26f1.png?width=216&crop=smart&auto=webp&s=a628fce38310683df11a3ef25bf2aa6462ac4409', 'width': 216}, {'height': 320, 'url': 'https://preview.redd.it/0npcuf7hg26f1.png?width=320&crop=smart&auto=webp&s=d0cd2dccadfd32b6ffa92139ca7b44473e0f94ea', 'width': 320}, {'height': 640, 'url': 'https://preview.redd.it/0npcuf7hg26f1.png?width=640&crop=smart&auto=webp&s=4c55f73cf38b629ae2c8880b26c06eda19948f88', 'width': 640}, {'height': 960, 'url': 'https://preview.redd.it/0npcuf7hg26f1.png?width=960&crop=smart&auto=webp&s=028af13b87d54a2ecbed63128afe25b1bfd9bd05', 'width': 960}, {'height': 1080, 'url': 'https://preview.redd.it/0npcuf7hg26f1.png?width=1080&crop=smart&auto=webp&s=452d81368beb62a206183e72267f2c72d8ceb28b', 'width': 1080}], 'source': {'height': 1080, 'url': 'https://preview.redd.it/0npcuf7hg26f1.png?auto=webp&s=d8406c9da2e6dbeea2af373885015eb51b8cec52', 'width': 1080}, 'variants': {}}]} |
||
Local Inference using llama.cpp on Unity - Nobodywho | 1 | [removed] | 2025-06-10T09:35:32 | https://www.reddit.com/r/LocalLLaMA/comments/1l7ufsd/local_inference_using_llamacpp_on_unity_nobodywho/ | No_Abbreviations_532 | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1l7ufsd | false | null | t3_1l7ufsd | /r/LocalLLaMA/comments/1l7ufsd/local_inference_using_llamacpp_on_unity_nobodywho/ | false | false | self | 1 | {'enabled': False, 'images': [{'id': 'b-NLMPLAOcZS1vaivS604O1hD3C8rg2sL58fBYrB4TU', 'resolutions': [{'height': 54, 'url': 'https://external-preview.redd.it/LwMg0CoATD9RMDX1yRkXW3PkB6-epQAGx4xfUfKRJFE.jpg?width=108&crop=smart&auto=webp&s=f91ca4caafba34ba84ad8b92726027b05cd45ad3', 'width': 108}, {'height': 108, 'url': 'https://external-preview.redd.it/LwMg0CoATD9RMDX1yRkXW3PkB6-epQAGx4xfUfKRJFE.jpg?width=216&crop=smart&auto=webp&s=8819f3556e6bd4c3b7660f04e591682580d8cb11', 'width': 216}, {'height': 160, 'url': 'https://external-preview.redd.it/LwMg0CoATD9RMDX1yRkXW3PkB6-epQAGx4xfUfKRJFE.jpg?width=320&crop=smart&auto=webp&s=e1a0107bbe73bec36d6569fe3d26c24416a92140', 'width': 320}, {'height': 320, 'url': 'https://external-preview.redd.it/LwMg0CoATD9RMDX1yRkXW3PkB6-epQAGx4xfUfKRJFE.jpg?width=640&crop=smart&auto=webp&s=beb79b2c1f5ca21954777697b0c51be18fd5b268', 'width': 640}, {'height': 480, 'url': 'https://external-preview.redd.it/LwMg0CoATD9RMDX1yRkXW3PkB6-epQAGx4xfUfKRJFE.jpg?width=960&crop=smart&auto=webp&s=87d2f5f5b0f54405667e398cd882702f204efbd4', 'width': 960}, {'height': 540, 'url': 'https://external-preview.redd.it/LwMg0CoATD9RMDX1yRkXW3PkB6-epQAGx4xfUfKRJFE.jpg?width=1080&crop=smart&auto=webp&s=5b46a3e42d316833df13540ca1f804cf0edaf76e', 'width': 1080}], 'source': {'height': 600, 'url': 'https://external-preview.redd.it/LwMg0CoATD9RMDX1yRkXW3PkB6-epQAGx4xfUfKRJFE.jpg?auto=webp&s=cefd4be11f75ac695281e5f3107a4b57dcf11e2e', 'width': 1200}, 'variants': {}}]} |
Having trouble deciding on model(s) for research assistance & image generation | 1 | Hi,
I've recently put together a new PC that I would like to use for running local AI models and for streaming games to my Steam Deck. For reference, the PC has an RTX 5060ti (16 GB VRAM), a Ryzen 7 5700x and 32 GB RAM, and is running Windows 11.
Regarding the AI part, I would like to interact with the AI models from laptops (and maybe phones?) on my home network, rather than from the PC directly. I don't expect any huge concurrent usage, just me and my fiancee taking turns at working with the AI.
I am not really sure where to get started for my AI use cases. I have downloaded Ollama on my PC and I was able to connect to it from my networked laptop via Chatbox. But I'm not sure how to set up these features:
- having the AI keep a kind of local knowledge base made up of scientific articles (PDFs mostly) that I feed it, so I can query it about those articles
- being able to attach PDFs to the AI chat window and have it summarize them or extract information from them
- having (free) access to online search engines like Wikipedia and DuckDuckGo
- generating images (once in a blue moon, but nice to have; won't be doing both scientific research and image generation at the same time)
Also, I am not even sure which models to use. I've tried asking Grok and Claude for recommendations, but they each recommend different models (e.g., for research Grok recommended Ollama 3 8b, Claude recommended Ollama 3.1 70b Q4 quantized). I'm not sure what to pick. I'm also not sure how to set up quantized models.
I am also not sure if it's possible to have research assistance and image generation available under the same UI. Ideally, I'd like a flow similar to Grok or ChatGPT's websites; I'm okay with writing a local website if need be.
I am a tech-savvy person, but I am very new to the local AI world. Up until now, I've only worked with paid models like Claude and so on. I would appreciate any pointers to help me get started.
So, is there any guide or any reference to get me started down this road?
| 2025-06-10T10:06:24 | https://www.reddit.com/r/LocalLLaMA/comments/1l7uws7/having_trouble_deciding_on_models_for_research/ | Senekrum | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1l7uws7 | false | null | t3_1l7uws7 | /r/LocalLLaMA/comments/1l7uws7/having_trouble_deciding_on_models_for_research/ | false | false | self | 1 | null |
Having trouble setting up local LLM(s) for research assistance and image generation | 2 | Hi,
I've recently put together a new PC that I would like to use for running local AI models and for streaming games to my Steam Deck. For reference, the PC has an RTX 5060ti (16 GB VRAM), a Ryzen 7 5700x and 32 GB RAM, and is running Windows 11.
Regarding the AI part, I would like to interact with the AI models from laptops (and maybe phones?) on my home network, rather than from the PC directly. I don't expect any huge concurrent usage, just me and my fiancee taking turns at working with the AI.
I am not really sure where to get started for my AI use cases. I have downloaded Ollama on my PC and I was able to connect to it from my networked laptop via Chatbox. But I'm not sure how to set up these features:
- having the AI keep a kind of local knowledge base made up of scientific articles (PDFs mostly) that I feed it, so I can query it about those articles
- being able to attach PDFs to the AI chat window and have it summarize them or extract information from them
- having (free) access to online search engines like Wikipedia and DuckDuckGo
- generating images (once in a blue moon, but nice to have; won't be doing both scientific research and image generation at the same time)
Also, I am not even sure which models to use. I've tried asking Grok and Claude for recommendations, but they each recommend different models (e.g., for research Grok recommended Ollama 3 8b, Claude recommended Ollama 3.1 70b Q4 quantized). I'm not sure what to pick. I'm also not sure how to set up quantized models.
I am also not sure if it's possible to have research assistance and image generation available under the same UI. Ideally, I'd like a flow similar to Grok or ChatGPT's websites; I'm okay with writing a local website if need be.
I am a tech-savvy person, but I am very new to the local AI world. Up until now, I've only worked with paid models like Claude and so on. I would appreciate any pointers to help me get started.
So, is there any guide or any reference to get me started down this road?
Thanks very much for your help.
| 2025-06-10T10:07:26 | https://www.reddit.com/r/LocalLLaMA/comments/1l7uxda/having_trouble_setting_up_local_llms_for_research/ | Senekrum | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1l7uxda | false | null | t3_1l7uxda | /r/LocalLLaMA/comments/1l7uxda/having_trouble_setting_up_local_llms_for_research/ | false | false | self | 2 | null |
An autonomous multi-turn tool-calling base model for RL agent training | 1 | [removed] | 2025-06-10T10:24:16 | https://huggingface.co/eliuakk/mirau-agent-14b-base | EliaukMouse | huggingface.co | 1970-01-01T00:00:00 | 0 | {} | 1l7v74d | false | null | t3_1l7v74d | /r/LocalLLaMA/comments/1l7v74d/an_autonomous_multiturn_toolcalling_base_model/ | false | false | 1 | {'enabled': False, 'images': [{'id': 'AKaMSOfJYnlG078czfFbfWqAb0eBPGDcHKrAXmnU50U', 'resolutions': [{'height': 58, 'url': 'https://external-preview.redd.it/dNdqJyhtXwj87G8KuNit74iQ4LPkok_1Pa60DPDQATc.jpg?width=108&crop=smart&auto=webp&s=e9e90a25625ad3f9171819c90d87173ce47b20aa', 'width': 108}, {'height': 116, 'url': 'https://external-preview.redd.it/dNdqJyhtXwj87G8KuNit74iQ4LPkok_1Pa60DPDQATc.jpg?width=216&crop=smart&auto=webp&s=113d5a22c282559523f7071bd18f075a1adeb4fe', 'width': 216}, {'height': 172, 'url': 'https://external-preview.redd.it/dNdqJyhtXwj87G8KuNit74iQ4LPkok_1Pa60DPDQATc.jpg?width=320&crop=smart&auto=webp&s=ca0236d18c5925fed7b96bf162c169d2f4631e11', 'width': 320}, {'height': 345, 'url': 'https://external-preview.redd.it/dNdqJyhtXwj87G8KuNit74iQ4LPkok_1Pa60DPDQATc.jpg?width=640&crop=smart&auto=webp&s=f843f791022421e80147e86ad1a24e06209b5cd8', 'width': 640}, {'height': 518, 'url': 'https://external-preview.redd.it/dNdqJyhtXwj87G8KuNit74iQ4LPkok_1Pa60DPDQATc.jpg?width=960&crop=smart&auto=webp&s=9cea9d6b43507fab2619a1dbe1414da6bda156de', 'width': 960}, {'height': 583, 'url': 'https://external-preview.redd.it/dNdqJyhtXwj87G8KuNit74iQ4LPkok_1Pa60DPDQATc.jpg?width=1080&crop=smart&auto=webp&s=cc2d248c7d109c6e62b2de9fe7b74127bb26a91b', 'width': 1080}], 'source': {'height': 648, 'url': 'https://external-preview.redd.it/dNdqJyhtXwj87G8KuNit74iQ4LPkok_1Pa60DPDQATc.jpg?auto=webp&s=8b4c2d15714bbf7cf2f67fabe38467149a7fb69c', 'width': 1200}, 'variants': {}}]} |
|
A multi-turn tool-calling base model for RL agent training | 11 | 2025-06-10T10:28:22 | https://huggingface.co/eliuakk/mirau-agent-14b-base | EliaukMouse | huggingface.co | 1970-01-01T00:00:00 | 0 | {} | 1l7v9gf | false | null | t3_1l7v9gf | /r/LocalLLaMA/comments/1l7v9gf/a_multiturn_toolcalling_base_model_for_rl_agent/ | false | false | 11 | {'enabled': False, 'images': [{'id': 'AKaMSOfJYnlG078czfFbfWqAb0eBPGDcHKrAXmnU50U', 'resolutions': [{'height': 58, 'url': 'https://external-preview.redd.it/dNdqJyhtXwj87G8KuNit74iQ4LPkok_1Pa60DPDQATc.jpg?width=108&crop=smart&auto=webp&s=e9e90a25625ad3f9171819c90d87173ce47b20aa', 'width': 108}, {'height': 116, 'url': 'https://external-preview.redd.it/dNdqJyhtXwj87G8KuNit74iQ4LPkok_1Pa60DPDQATc.jpg?width=216&crop=smart&auto=webp&s=113d5a22c282559523f7071bd18f075a1adeb4fe', 'width': 216}, {'height': 172, 'url': 'https://external-preview.redd.it/dNdqJyhtXwj87G8KuNit74iQ4LPkok_1Pa60DPDQATc.jpg?width=320&crop=smart&auto=webp&s=ca0236d18c5925fed7b96bf162c169d2f4631e11', 'width': 320}, {'height': 345, 'url': 'https://external-preview.redd.it/dNdqJyhtXwj87G8KuNit74iQ4LPkok_1Pa60DPDQATc.jpg?width=640&crop=smart&auto=webp&s=f843f791022421e80147e86ad1a24e06209b5cd8', 'width': 640}, {'height': 518, 'url': 'https://external-preview.redd.it/dNdqJyhtXwj87G8KuNit74iQ4LPkok_1Pa60DPDQATc.jpg?width=960&crop=smart&auto=webp&s=9cea9d6b43507fab2619a1dbe1414da6bda156de', 'width': 960}, {'height': 583, 'url': 'https://external-preview.redd.it/dNdqJyhtXwj87G8KuNit74iQ4LPkok_1Pa60DPDQATc.jpg?width=1080&crop=smart&auto=webp&s=cc2d248c7d109c6e62b2de9fe7b74127bb26a91b', 'width': 1080}], 'source': {'height': 648, 'url': 'https://external-preview.redd.it/dNdqJyhtXwj87G8KuNit74iQ4LPkok_1Pa60DPDQATc.jpg?auto=webp&s=8b4c2d15714bbf7cf2f67fabe38467149a7fb69c', 'width': 1200}, 'variants': {}}]} |
||
What is the cheapest setup to host devstral model and use this server on lan network for coding at home? | 1 | [removed] | 2025-06-10T11:00:09 | https://www.reddit.com/r/LocalLLaMA/comments/1l7vsf2/what_is_the_cheapest_setup_to_host_devstral_model/ | PreparationTrue9138 | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1l7vsf2 | false | null | t3_1l7vsf2 | /r/LocalLLaMA/comments/1l7vsf2/what_is_the_cheapest_setup_to_host_devstral_model/ | false | false | self | 1 | null |
i am using nvidia/Llama-3.1-Nemotron-Nano-VL-8B-V1 after cloning all its file its unable to find dual_hybrid_vit.py' but in hugging face in files section i am not getting dual_hybrid_vit.py file. but I'm unable to find why its getting this error or how i solve this error. | 1 | [removed] | 2025-06-10T11:29:03 | https://www.reddit.com/r/LocalLLaMA/comments/1l7wb3t/i_am_using_nvidiallama31nemotronnanovl8bv1_after/ | Unique_Plenty_5261 | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1l7wb3t | false | null | t3_1l7wb3t | /r/LocalLLaMA/comments/1l7wb3t/i_am_using_nvidiallama31nemotronnanovl8bv1_after/ | false | false | self | 1 | null |
Data prep using natural language prompts | 1 | [removed] | 2025-06-10T11:47:19 | https://www.reddit.com/r/LocalLLaMA/comments/1l7wn62/data_prep_using_natural_language_prompts/ | FitImprovement3420 | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1l7wn62 | false | null | t3_1l7wn62 | /r/LocalLLaMA/comments/1l7wn62/data_prep_using_natural_language_prompts/ | false | false | self | 1 | null |
SERAX is a text data format built for AI-generated content. | 19 | 2025-06-10T11:48:07 | https://github.com/vantige-ai/serax | Mundane_Ad8936 | github.com | 1970-01-01T00:00:00 | 0 | {} | 1l7wnpe | false | null | t3_1l7wnpe | /r/LocalLLaMA/comments/1l7wnpe/serax_is_a_text_data_format_built_for_aigenerated/ | false | false | 19 | {'enabled': False, 'images': [{'id': 'WfO101n2RsEpq2JqpztWVhwPv1HD0w3Zti1pwhIgaDc', 'resolutions': [{'height': 54, 'url': 'https://external-preview.redd.it/iPoqUSVp4rUtU8gZ1RTlqBQPVZg8eaEZ2QFMKyFv5z4.jpg?width=108&crop=smart&auto=webp&s=5be071e7029f33372ca937bb38419059ed100b4b', 'width': 108}, {'height': 108, 'url': 'https://external-preview.redd.it/iPoqUSVp4rUtU8gZ1RTlqBQPVZg8eaEZ2QFMKyFv5z4.jpg?width=216&crop=smart&auto=webp&s=a38f317542c348e022c59a1f94ca94d971caeb30', 'width': 216}, {'height': 160, 'url': 'https://external-preview.redd.it/iPoqUSVp4rUtU8gZ1RTlqBQPVZg8eaEZ2QFMKyFv5z4.jpg?width=320&crop=smart&auto=webp&s=5b1b8ae2559f86ba92b72784d0d5bf9a21a1c275', 'width': 320}, {'height': 320, 'url': 'https://external-preview.redd.it/iPoqUSVp4rUtU8gZ1RTlqBQPVZg8eaEZ2QFMKyFv5z4.jpg?width=640&crop=smart&auto=webp&s=250ad2675bd529f48ef6d26fef6df71d2ea0ec6d', 'width': 640}, {'height': 480, 'url': 'https://external-preview.redd.it/iPoqUSVp4rUtU8gZ1RTlqBQPVZg8eaEZ2QFMKyFv5z4.jpg?width=960&crop=smart&auto=webp&s=a95fa677fff0e3edf539c83484544ccc68b3efcb', 'width': 960}, {'height': 540, 'url': 'https://external-preview.redd.it/iPoqUSVp4rUtU8gZ1RTlqBQPVZg8eaEZ2QFMKyFv5z4.jpg?width=1080&crop=smart&auto=webp&s=b0c15564d90465eda3d3463690c1ae8bb6bf08b9', 'width': 1080}], 'source': {'height': 600, 'url': 'https://external-preview.redd.it/iPoqUSVp4rUtU8gZ1RTlqBQPVZg8eaEZ2QFMKyFv5z4.jpg?auto=webp&s=3783051abd697c4e2a68d3e60c490b8722a410c7', 'width': 1200}, 'variants': {}}]} |
||
Data manipulation using natural language prompts | 1 | [removed] | 2025-06-10T11:50:43 | https://www.reddit.com/r/LocalLLaMA/comments/1l7wphl/data_manipulation_using_natural_language_prompts/ | Informal_Exit3592 | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1l7wphl | false | null | t3_1l7wphl | /r/LocalLLaMA/comments/1l7wphl/data_manipulation_using_natural_language_prompts/ | false | false | self | 1 | null |
Data manipulation using natural language prompts | 1 | [removed] | 2025-06-10T11:57:15 | https://www.reddit.com/r/LocalLLaMA/comments/1l7wtux/data_manipulation_using_natural_language_prompts/ | felixbrockm | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1l7wtux | false | null | t3_1l7wtux | /r/LocalLLaMA/comments/1l7wtux/data_manipulation_using_natural_language_prompts/ | false | false | self | 1 | null |
Computer Agent - a Hugging Face Space by smolagents | 4 | Is there a repo for this implementation? | 2025-06-10T11:58:29 | https://huggingface.co/spaces/smolagents/computer-agent | mr_house7 | huggingface.co | 1970-01-01T00:00:00 | 0 | {} | 1l7wuou | false | null | t3_1l7wuou | /r/LocalLLaMA/comments/1l7wuou/computer_agent_a_hugging_face_space_by_smolagents/ | false | false | 4 | {'enabled': False, 'images': [{'id': 'HjhlQ-8BnpJ0ISZyBPdoajtdv6gZl6Lmx-LVmqi0ogY', 'resolutions': [{'height': 58, 'url': 'https://external-preview.redd.it/HjhlQ-8BnpJ0ISZyBPdoajtdv6gZl6Lmx-LVmqi0ogY.png?width=108&crop=smart&auto=webp&s=8d63bbfebee38f767854629e96d9f0be8abff6be', 'width': 108}, {'height': 116, 'url': 'https://external-preview.redd.it/HjhlQ-8BnpJ0ISZyBPdoajtdv6gZl6Lmx-LVmqi0ogY.png?width=216&crop=smart&auto=webp&s=695c209891bd556daf19628aa84395c3959660aa', 'width': 216}, {'height': 172, 'url': 'https://external-preview.redd.it/HjhlQ-8BnpJ0ISZyBPdoajtdv6gZl6Lmx-LVmqi0ogY.png?width=320&crop=smart&auto=webp&s=ea4f50225e7e15372cc307efcecbb4ef93c887a3', 'width': 320}, {'height': 345, 'url': 'https://external-preview.redd.it/HjhlQ-8BnpJ0ISZyBPdoajtdv6gZl6Lmx-LVmqi0ogY.png?width=640&crop=smart&auto=webp&s=1cbc9041e2665704bb348ebd90cd258b532af68d', 'width': 640}, {'height': 518, 'url': 'https://external-preview.redd.it/HjhlQ-8BnpJ0ISZyBPdoajtdv6gZl6Lmx-LVmqi0ogY.png?width=960&crop=smart&auto=webp&s=e08ad6bb511f7e8a82cce2495f56a48310ea38ec', 'width': 960}, {'height': 583, 'url': 'https://external-preview.redd.it/HjhlQ-8BnpJ0ISZyBPdoajtdv6gZl6Lmx-LVmqi0ogY.png?width=1080&crop=smart&auto=webp&s=cbad946ec80b6158e973b5e1c327e722b96baf69', 'width': 1080}], 'source': {'height': 648, 'url': 'https://external-preview.redd.it/HjhlQ-8BnpJ0ISZyBPdoajtdv6gZl6Lmx-LVmqi0ogY.png?auto=webp&s=89e74d93fd33e47c1bb93875272c288503116b5e', 'width': 1200}, 'variants': {}}]} |
|
MiniCPM4: Ultra-Efficient LLMs on End Devices | 48 | MiniCPM4 has arrived on Hugging Face
A new family of ultra-efficient large language models (LLMs) explicitly designed for end-side devices.
Paper : [https://huggingface.co/papers/2506.07900](https://huggingface.co/papers/2506.07900)
Weights : [https://huggingface.co/collections/openbmb/minicpm4-6841ab29d180257e940baa9b](https://huggingface.co/collections/openbmb/minicpm4-6841ab29d180257e940baa9b) | 2025-06-10T12:31:22 | https://www.reddit.com/r/LocalLLaMA/comments/1l7xick/minicpm4_ultraefficient_llms_on_end_devices/ | ApprehensiveAd3629 | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1l7xick | false | null | t3_1l7xick | /r/LocalLLaMA/comments/1l7xick/minicpm4_ultraefficient_llms_on_end_devices/ | false | false | self | 48 | {'enabled': False, 'images': [{'id': 'Mvyoq4hv-EqNr10e7oaPVziEw5PJv8pWhAG6S3xkjww', 'resolutions': [{'height': 58, 'url': 'https://external-preview.redd.it/h7tU0a98XOaOcpxFdgSezJ1Tn5HImlax4fNZhDNw0wc.jpg?width=108&crop=smart&auto=webp&s=7a5c6334bd5e8076dad0e7917086f6067715837d', 'width': 108}, {'height': 116, 'url': 'https://external-preview.redd.it/h7tU0a98XOaOcpxFdgSezJ1Tn5HImlax4fNZhDNw0wc.jpg?width=216&crop=smart&auto=webp&s=3e2679f7e8720703857b25145050a46b60cf1f77', 'width': 216}, {'height': 172, 'url': 'https://external-preview.redd.it/h7tU0a98XOaOcpxFdgSezJ1Tn5HImlax4fNZhDNw0wc.jpg?width=320&crop=smart&auto=webp&s=eabbc471890a42eb34bcf21e6c17bce323b8b5cc', 'width': 320}, {'height': 345, 'url': 'https://external-preview.redd.it/h7tU0a98XOaOcpxFdgSezJ1Tn5HImlax4fNZhDNw0wc.jpg?width=640&crop=smart&auto=webp&s=6f32b1f215af1b69aa419ce50da59a6cff13e41b', 'width': 640}, {'height': 518, 'url': 'https://external-preview.redd.it/h7tU0a98XOaOcpxFdgSezJ1Tn5HImlax4fNZhDNw0wc.jpg?width=960&crop=smart&auto=webp&s=2bae5a2d8353f440102a6a0589add3ab4d40f72f', 'width': 960}, {'height': 583, 'url': 'https://external-preview.redd.it/h7tU0a98XOaOcpxFdgSezJ1Tn5HImlax4fNZhDNw0wc.jpg?width=1080&crop=smart&auto=webp&s=4a95e4f36b768a245919d2454e1bffcc405a97fa', 'width': 1080}], 'source': {'height': 648, 'url': 'https://external-preview.redd.it/h7tU0a98XOaOcpxFdgSezJ1Tn5HImlax4fNZhDNw0wc.jpg?auto=webp&s=580ca01bf3f3a6707204be72ddafe6eb956af6ea', 'width': 1200}, 'variants': {}}]} |
Help me!!! | 1 | [removed] | 2025-06-10T13:08:31 | https://www.reddit.com/r/LocalLLaMA/comments/1l7yarp/help_me/ | novamaster696969 | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1l7yarp | false | null | t3_1l7yarp | /r/LocalLLaMA/comments/1l7yarp/help_me/ | false | false | self | 1 | null |
SOTA for table info extraction? | 3 | Hi Everyone
I need to locally (or securely on a cloud) run a model that extracts data from a table. the table has a nested structure.
I have run InternVL3 78B awq. It works okay, it sometimes misses data or screws up the order. Most annoyingly though it just misspells certain product names rather than outputting an exact replica of the source. It's almost like it slightly hallucinates, but it could be down how to the vision model is receiving the png? I am not sure whether its a code issue or a model choice issue. Or whether anything can be done at all!
Its quite annoying really - i've run many simple programs trying to extract this info accurately (paddle ocr, textract, tabula, powerquery etc) but there's always slight issues with each! I thought it would be simple.
Anyway, any insight or suggestions are very welcome. I have about 150gb vram. I cant share the exact code but this is essentially it:
import os
import json
import time
from pathlib import Path
from PIL import Image
from tqdm import tqdm
# Note: The vllm and transformers libraries need to be installed.
# pip install vllm transformers torch torchvision torchaudio Pillow
from vllm import LLM, SamplingParams
from transformers import AutoTokenizer
# --- Main processing function ---
def run_inference():
"""
This function contains the core logic for loading data, processing it in batches
with a VLLM model, and saving the results.
"""
# --- 1. Model and VLLM Configuration ---
# TODO: User should replace this with their actual model ID.
MODEL_ID = "your/model-id-here"
MAX_MODEL_LEN = 10000
# Set any necessary environment variables for VLLM
os.environ['VLLM_ATTENTION_BACKEND'] = "FLASHINFER"
print(f"Initializing LLM with model: {MODEL_ID}")
llm = LLM(
model=MODEL_ID,
gpu_memory_utilization=.95,
max_model_len=MAX_MODEL_LEN,
dtype="float16",
enforce_eager=True,
trust_remote_code=True,
kv_cache_dtype="fp8",
quantization="awq",
tensor_parallel_size=1,
limit_mm_per_prompt="image=1,video=0"
)
# --- 2. Anonymized Prompt Templates and Examples ---
# This dictionary holds the structure for different document types.
prompt_dict = {
"document_type_A": {
"fields": [
"Field1", "Field2", "Field3", "Field4", "Field5", "Field6",
"Field7", "Field8", "Field9", "Field10", "Field11", "Field12",
"Field13", "Field14", "Field15", "Field16", "Field17", "Field18"
],
"json": [
{
"Field1": "Value 1", "Field2": "Some Company Inc.", "Field3": "2023-01-01",
"Field4": "INV-12345", "Field5": "SKU-001", "Field6": "300",
"Field7": "Product A", "Field8": "10.50", "Field9": "3150.00",
"Field10": "Box", "Field11": "0", "Field12": "0.00",
"Field13": "BATCH-XYZ", "Field14": "550.00", "Field15": "5500.00",
"Field16": "0.00", "Field17": "6050.00", "Field18": "123456789"
},
{
"Field1": "Value 1", "Field2": "Some Company Inc.", "Field3": "2023-01-01",
"Field4": "INV-12345", "Field5": "SKU-002", "Field6": "2000",
"Field7": "Product B", "Field8": "1.25", "Field9": "2500.00",
"Field10": "Unit", "Field11": "0", "Field12": "0.00",
"Field13": "BATCH-ABC", "Field14": "550.00", "Field15": "5500.00",
"Field16": "0.00", "Field17": "6050.00", "Field18": "123456789"
}
]
},
"document_type_B": {
"fields": ["ID", "Officer", "Destination", "ItemNo", "ItemName", "AssetPrice", "Quantity", "Price", "Unit"],
"json": [
{"ID": "21341", "Officer": "John Doe", "Destination": "Main Warehouse", "ItemNo": 1, "ItemName": "Product C", "AssetPrice": "", "Quantity": "25", "Price": "12.31", "Unit": "BOTTLE"},
{"ID": "", "Officer": "Jane Smith", "Destination": "Branch Office", "ItemNo": 5, "ItemName": "Product D", "AssetPrice": "", "Quantity": "125", "Price": "142.31", "Unit": "TABLET"}
]
}
}
# --- 3. Image Loading ---
# TODO: User should place their image files in this directory.
IMAGE_DIRECTORY = "./images_to_process"
processed_data = []
image_dir = Path(IMAGE_DIRECTORY)
if not image_dir.exists():
print(f"Error: Image directory not found at '{IMAGE_DIRECTORY}'")
print("Please create it and add your images.")
return
print(f"Loading images from '{IMAGE_DIRECTORY}'...")
image_files = list(image_dir.glob('*.jpg')) + list(image_dir.glob('*.jpeg')) + list(image_dir.glob('*.png'))
for p in tqdm(image_files, desc="Loading images"):
processed_data.append({
"filename": p.name,
"image_object": Image.open(p).convert("RGB")
})
print(f"Loaded {len(processed_data)} images.")
if not processed_data:
print("No images found to process. Exiting.")
return
# --- 4. Prompt Generation and Batch Processing ---
extraction_instruction = """<image>
Analyze the document in the image. Your task is to extract information into a structured JSON list based on the fields provided.
Your goal is to identify every distinct item row in the main table. For **each and every item row**, you will create one complete JSON object.
To do this correctly, follow this two-step process for each item:
1. **Identify Shared Information:** First, locate the information that is shared across all items. This data is usually at the top of the document (like `Field2`, `Field3`, `Field4`) or in the summary at the bottom (like `Field15`, `Field14`, `Field17`).
2. **Identify Row-Specific Information:** Second, extract the data that is unique to that specific item's row in the table (like `Field5`, `Field7`, `Field6`, `Field9`).
3. **Combine and Construct:** Finally, construct a single JSON object for that item. This object **must** contain both the shared information from step 1 and the row-specific information from step 2. The shared values must be repeated for every item's JSON object.
The fields to extract for each object are:
{ext}
If a value for a field cannot be found, use an empty string "" as seen in the document. You are copying the data verbatim making no changes or adjustments to the strings/numbers. Still copy data even if the value is "0".
Format the entire output as a single JSON list.
Here is an example of the expected output format, based on the first two items from the image:
{ex}
Remember: ONLY OUTPUT THE VALID JSON LIST. ALL VALUES SHOULD BE STRINGS. Do not include any text before or after the list."""
# VLLM Sampling Parameters
SAMPLING_TEMP = 0.8
MAX_NEW_TOKENS = MAX_MODEL_LEN - 1500
stop_tokens = ["<|endoftext|>", "<|im_start|>", "<|im_end|>"]
tokenizer = AutoTokenizer.from_pretrained(MODEL_ID, trust_remote_code=True)
stop_token_ids = [tokenizer.convert_tokens_to_ids(i) for i in stop_tokens]
sampling_params = SamplingParams(temperature=SAMPLING_TEMP, max_tokens=MAX_NEW_TOKENS, stop_token_ids=stop_token_ids)
# Batching Configuration
BATCH_SIZE = 8
all_results_with_filenames = []
batched_filenames_list = []
# This script will process all images using one document type.
# In the original script, this was hardcoded.
doc_type_key = "document_type_A"
print(f"Using prompt template for: '{doc_type_key}'")
# Pre-calculate parts of the prompt that are constant for the chosen document type
ext = ", ".join([f"'{field}'" for field in prompt_dict[doc_type_key]['fields']])
ex_str = json.dumps(prompt_dict[doc_type_key]['json'], indent=2)
user_content_for_group = extraction_instruction.replace("{ext}", ext).replace("{ex}", ex_str)
num_total_images = len(processed_data)
num_batches = (num_total_images + BATCH_SIZE - 1) // BATCH_SIZE
print(f"Starting generation for {num_total_images} images in {num_batches} batches...")
for i in tqdm(range(0, num_total_images, BATCH_SIZE), total=num_batches, desc=f"Processing batches"):
batch_image_items = processed_data[i:i + BATCH_SIZE]
if not batch_image_items:
continue
current_batch_messages = []
current_batch_filenames = [item['filename'] for item in batch_image_items]
batched_filenames_list.append(current_batch_filenames)
for image_item in batch_image_items:
# The user_content is the same for all images in this group
message_for_template = [{'role': 'user', 'content': user_content_for_group}]
prompt_text = tokenizer.apply_chat_template(
message_for_template,
tokenize=False,
add_generation_prompt=True
)
current_batch_messages.append({
"prompt": prompt_text,
"multi_modal_data": {"image": image_item['image_object']}
})
if not current_batch_messages:
continue
# Generate outputs for the entire batch
batch_model_outputs = llm.generate(current_batch_messages, sampling_params, use_tqdm=False)
# Associate outputs with filenames for this batch
for idx, model_output_item in enumerate(batch_model_outputs):
all_results_with_filenames.append({
"filename": current_batch_filenames[idx],
"generated_text": model_output_item.outputs[0].text
})
print("Finished generating all outputs.")
# --- 5. Save Results ---
# The original script encrypted the output. Here, we save it as a simple JSON file.
results_dir = "./output"
os.makedirs(results_dir, exist_ok=True)
# Save the main results
output_filename = os.path.join(results_dir, "extraction_results.json")
with open(output_filename, "w", encoding="utf-8") as f:
json.dump(all_results_with_filenames, f, indent=2, ensure_ascii=False)
print(f"Saved all results to {output_filename}")
# Save the list of filenames per batch
filenames_output_path = os.path.join(results_dir, "batched_filenames.json")
with open(filenames_output_path, "w", encoding="utf-8") as f:
json.dump(batched_filenames_list, f, indent=2)
print(f"Saved batched filenames to {filenames_output_path}")
if __name__ == "__main__":
run_inference()
| 2025-06-10T13:15:52 | https://www.reddit.com/r/LocalLLaMA/comments/1l7ygph/sota_for_table_info_extraction/ | Moreh | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1l7ygph | false | null | t3_1l7ygph | /r/LocalLLaMA/comments/1l7ygph/sota_for_table_info_extraction/ | false | false | self | 3 | null |
Everything you wanted to know about Apple’s MLX | 72 | [https://www.youtube.com/watch?v=tn2Hvw7eCsw](https://www.youtube.com/watch?v=tn2Hvw7eCsw)
Cool you can do even dynamic quantization yourself?! Lots of little nuggets in this video. | 2025-06-10T13:29:35 | https://www.reddit.com/r/LocalLLaMA/comments/1l7yrni/everything_you_wanted_to_know_about_apples_mlx/ | Careless_Garlic1438 | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1l7yrni | false | null | t3_1l7yrni | /r/LocalLLaMA/comments/1l7yrni/everything_you_wanted_to_know_about_apples_mlx/ | false | false | self | 72 | {'enabled': False, 'images': [{'id': 'NjVHaItXS-TJ0D9-7VBRMbmd6mPnwXzdu7I9Q88qMUo', 'resolutions': [{'height': 81, 'url': 'https://external-preview.redd.it/CXs79lMk8eceG0fPpwyg9D7nrDHi5t7gL-0mSG2LgMY.jpg?width=108&crop=smart&auto=webp&s=613ba3115bddf648a7857d6332803fa2b3aa2464', 'width': 108}, {'height': 162, 'url': 'https://external-preview.redd.it/CXs79lMk8eceG0fPpwyg9D7nrDHi5t7gL-0mSG2LgMY.jpg?width=216&crop=smart&auto=webp&s=858ec7c15d1d8858137e6ec78b103b5ef451fad7', 'width': 216}, {'height': 240, 'url': 'https://external-preview.redd.it/CXs79lMk8eceG0fPpwyg9D7nrDHi5t7gL-0mSG2LgMY.jpg?width=320&crop=smart&auto=webp&s=85835401747fa5760ec276676a7514818b37bfa0', 'width': 320}], 'source': {'height': 360, 'url': 'https://external-preview.redd.it/CXs79lMk8eceG0fPpwyg9D7nrDHi5t7gL-0mSG2LgMY.jpg?auto=webp&s=3133c20800c5eed7322723c620d20dbd3c64afba', 'width': 480}, 'variants': {}}]} |
Data prep using natural language prompts | 1 | [removed] | 2025-06-10T13:36:52 | https://www.reddit.com/r/LocalLLaMA/comments/1l7yxj6/data_prep_using_natural_language_prompts/ | felixbrockm | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1l7yxj6 | false | null | t3_1l7yxj6 | /r/LocalLLaMA/comments/1l7yxj6/data_prep_using_natural_language_prompts/ | false | false | self | 1 | null |
Data prep using natural language prompts | 1 | [removed] | 2025-06-10T13:39:12 | https://www.reddit.com/r/LocalLLaMA/comments/1l7yzdv/data_prep_using_natural_language_prompts/ | felixbrockm | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1l7yzdv | false | null | t3_1l7yzdv | /r/LocalLLaMA/comments/1l7yzdv/data_prep_using_natural_language_prompts/ | false | false | self | 1 | null |
HDMI/DP Dummy Plugs for Multi-GPU Setups | 3 | Hey guys, quick question. I have a PC that I use for game streaming using sunshine and running local LLMs. I have an HDMI dummy plug on the graphics card to force hardware acceleration and allow sunshine to grab the frame buffer. I just dropped another graphics card in for additional VRAM to run larger LLM models locally. Do I need to use an HMDI dummy plug on the second card as well? Both GPU are 5070 Ti.
I've loaded a large model across both cards and can see the VRAM allocation on the second card is working. I'm just not sure if the GPU is working at 100% for PP and TG and I'm not entirely sure how I could make that determination.
I've watched the GPU effective clocks and PCIE link speed on HWINFO. Card 0 holds 32GT/s PCIE speed and 2,500mhz clock. GPU 1 will jump up to these values during prompt processing and token generation, then fall back down. GPU 0 is maintaining the stream which could explain why it stays active.
Anyway, I appreciate any help/thoughts you have. | 2025-06-10T14:05:10 | https://www.reddit.com/r/LocalLLaMA/comments/1l7zlgf/hdmidp_dummy_plugs_for_multigpu_setups/ | PuffyCake23 | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1l7zlgf | false | null | t3_1l7zlgf | /r/LocalLLaMA/comments/1l7zlgf/hdmidp_dummy_plugs_for_multigpu_setups/ | false | false | self | 3 | null |
mistralai/Magistral-Small-2506 | 477 | Building upon Mistral Small 3.1 (2503), **with added reasoning capabilities**, undergoing SFT from Magistral Medium traces and RL on top, it's a small, efficient reasoning model with 24B parameters.
Magistral Small can be deployed locally, fitting within a single RTX 4090 or a 32GB RAM MacBook once quantized.
Learn more about Magistral in Mistral's [blog post](https://mistral.ai/news/magistral/).
# Key Features
* **Reasoning:** Capable of long chains of reasoning traces before providing an answer.
* **Multilingual:** Supports dozens of languages, including English, French, German, Greek, Hindi, Indonesian, Italian, Japanese, Korean, Malay, Nepali, Polish, Portuguese, Romanian, Russian, Serbian, Spanish, Swedish, Turkish, Ukrainian, Vietnamese, Arabic, Bengali, Chinese, and Farsi.
* **Apache 2.0 License:** Open license allowing usage and modification for both commercial and non-commercial purposes.
* **Context Window:** A 128k context window, **but** performance might degrade past **40k**. Hence we recommend setting the maximum model length to 40k.
# Benchmark Results
|Model|AIME24 pass@1|AIME25 pass@1|GPQA Diamond|Livecodebench (v5)|
|:-|:-|:-|:-|:-|
|Magistral Medium|73.59%|64.95%|70.83%|59.36%|
|Magistral Small|70.68%|62.76%|68.18%|55.84%| | 2025-06-10T14:16:58 | https://huggingface.co/mistralai/Magistral-Small-2506 | yoracale | huggingface.co | 1970-01-01T00:00:00 | 0 | {} | 1l7zvph | false | null | t3_1l7zvph | /r/LocalLLaMA/comments/1l7zvph/mistralaimagistralsmall2506/ | false | false | default | 477 | null |
New open-weight reasoning model from Mistral | 422 | https://mistral.ai/news/magistral
And the paper : https://mistral.ai/static/research/magistral.pdf
What are your thoughts ? | 2025-06-10T14:20:17 | https://www.reddit.com/r/LocalLLaMA/comments/1l7zyk2/new_openweight_reasoning_model_from_mistral/ | AdIllustrious436 | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1l7zyk2 | false | null | t3_1l7zyk2 | /r/LocalLLaMA/comments/1l7zyk2/new_openweight_reasoning_model_from_mistral/ | false | false | self | 422 | {'enabled': False, 'images': [{'id': 'QLQU1soiMTzFAm8GzW6EPDbaX5jrcYYFqy1ql5NYoiQ', 'resolutions': [{'height': 56, 'url': 'https://external-preview.redd.it/UDZBQmD4AJb2vSY-B7oM2DhQ3zjGzTcUOviRMRcUKkg.jpg?width=108&crop=smart&auto=webp&s=bf2fc6d6ae14adad4ce62ffea575abc3783778db', 'width': 108}, {'height': 113, 'url': 'https://external-preview.redd.it/UDZBQmD4AJb2vSY-B7oM2DhQ3zjGzTcUOviRMRcUKkg.jpg?width=216&crop=smart&auto=webp&s=4a5f46c5464cea72c64df6c73d58b15e102c5936', 'width': 216}, {'height': 168, 'url': 'https://external-preview.redd.it/UDZBQmD4AJb2vSY-B7oM2DhQ3zjGzTcUOviRMRcUKkg.jpg?width=320&crop=smart&auto=webp&s=aa1e4abc763404a25bda9d60fe6440b747d6bae4', 'width': 320}, {'height': 336, 'url': 'https://external-preview.redd.it/UDZBQmD4AJb2vSY-B7oM2DhQ3zjGzTcUOviRMRcUKkg.jpg?width=640&crop=smart&auto=webp&s=122efd46018c04117aca71d80db3640d390428bd', 'width': 640}, {'height': 504, 'url': 'https://external-preview.redd.it/UDZBQmD4AJb2vSY-B7oM2DhQ3zjGzTcUOviRMRcUKkg.jpg?width=960&crop=smart&auto=webp&s=b53cfe1770ee2b37ce0f5b5e1b0fd67d3276a350', 'width': 960}, {'height': 567, 'url': 'https://external-preview.redd.it/UDZBQmD4AJb2vSY-B7oM2DhQ3zjGzTcUOviRMRcUKkg.jpg?width=1080&crop=smart&auto=webp&s=278352f076c5bbdf8f6e7cecedab77d8794332ff', 'width': 1080}], 'source': {'height': 2520, 'url': 'https://external-preview.redd.it/UDZBQmD4AJb2vSY-B7oM2DhQ3zjGzTcUOviRMRcUKkg.jpg?auto=webp&s=691d56b882a79feffdb4b780dc6a0db1b2c5d709', 'width': 4800}, 'variants': {}}]} |
Magistral — the first reasoning model by Mistral AI | 148 | 2025-06-10T14:30:17 | https://www.reddit.com/r/LocalLLaMA/comments/1l807c0/magistral_the_first_reasoning_model_by_mistral_ai/ | touhidul002 | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1l807c0 | false | null | t3_1l807c0 | /r/LocalLLaMA/comments/1l807c0/magistral_the_first_reasoning_model_by_mistral_ai/ | false | false | 148 | {'enabled': False, 'images': [{'id': 'jOibS74isPbVc3DLbufoOPDQCs1Ev133Bb9JGRu_e68', 'resolutions': [{'height': 58, 'url': 'https://external-preview.redd.it/wBetgDbEeci5oMW6w7naZxLP2OrsdY6hVvjhJ2wPr2o.jpg?width=108&crop=smart&auto=webp&s=bea26a8d982345591484abf0781095784ba28eaa', 'width': 108}, {'height': 116, 'url': 'https://external-preview.redd.it/wBetgDbEeci5oMW6w7naZxLP2OrsdY6hVvjhJ2wPr2o.jpg?width=216&crop=smart&auto=webp&s=228f8c7a9087efd88802a38a27b1459e0823a921', 'width': 216}, {'height': 172, 'url': 'https://external-preview.redd.it/wBetgDbEeci5oMW6w7naZxLP2OrsdY6hVvjhJ2wPr2o.jpg?width=320&crop=smart&auto=webp&s=1f415c579d3707f639e01d806376d663ad999810', 'width': 320}, {'height': 345, 'url': 'https://external-preview.redd.it/wBetgDbEeci5oMW6w7naZxLP2OrsdY6hVvjhJ2wPr2o.jpg?width=640&crop=smart&auto=webp&s=8e441d45d84498bd6b2be4adfe5a6738bbb82ed7', 'width': 640}, {'height': 518, 'url': 'https://external-preview.redd.it/wBetgDbEeci5oMW6w7naZxLP2OrsdY6hVvjhJ2wPr2o.jpg?width=960&crop=smart&auto=webp&s=2a7a7b1bc9e7189c2c70d683ae819a4ebcf9c302', 'width': 960}, {'height': 583, 'url': 'https://external-preview.redd.it/wBetgDbEeci5oMW6w7naZxLP2OrsdY6hVvjhJ2wPr2o.jpg?width=1080&crop=smart&auto=webp&s=517492f52e3d25fe902b794690a33a0f2fa44c54', 'width': 1080}], 'source': {'height': 648, 'url': 'https://external-preview.redd.it/wBetgDbEeci5oMW6w7naZxLP2OrsdY6hVvjhJ2wPr2o.jpg?auto=webp&s=d7d7d2329543a3544901f4ecb77ac2bac50a271b', 'width': 1200}, 'variants': {}}]} |
||
Get Claude at Home - New UI generation model for Components and Tailwind with 32B, 14B, 8B, 4B | 234 | 2025-06-10T14:31:57 | https://v.redd.it/y74jt9x2y36f1 | United-Rush4073 | v.redd.it | 1970-01-01T00:00:00 | 0 | {} | 1l808xc | false | {'reddit_video': {'bitrate_kbps': 5000, 'dash_url': 'https://v.redd.it/y74jt9x2y36f1/DASHPlaylist.mpd?a=1752157929%2CMTg1NmM3OTJiODU0ZGM0ZjJhZDBlNzA5NTFmNzcyZDRmOTU1OWE2YmMwNGE0ZTM3OWE5YjlhMTEwZjhjOTRkYQ%3D%3D&v=1&f=sd', 'duration': 30, 'fallback_url': 'https://v.redd.it/y74jt9x2y36f1/DASH_1080.mp4?source=fallback', 'has_audio': True, 'height': 1080, 'hls_url': 'https://v.redd.it/y74jt9x2y36f1/HLSPlaylist.m3u8?a=1752157929%2CYWYzNDFmOTBkMTgzN2ViYTdiOTE3ODZhNzE3OWE2ZjkwMTAwNzE2ZmQwZDI2NDRjZjFhMWEzYTE4Y2FkNmY2Mg%3D%3D&v=1&f=sd', 'is_gif': False, 'scrubber_media_url': 'https://v.redd.it/y74jt9x2y36f1/DASH_96.mp4', 'transcoding_status': 'completed', 'width': 1920}} | t3_1l808xc | /r/LocalLLaMA/comments/1l808xc/get_claude_at_home_new_ui_generation_model_for/ | false | false | 234 | {'enabled': False, 'images': [{'id': 'b2RsbXo5eDJ5MzZmMRaVPCH-YMXWS5H8theQIxqXDZAve_bVCKxOsnpVL7to', 'resolutions': [{'height': 60, 'url': 'https://external-preview.redd.it/b2RsbXo5eDJ5MzZmMRaVPCH-YMXWS5H8theQIxqXDZAve_bVCKxOsnpVL7to.png?width=108&crop=smart&format=pjpg&auto=webp&s=7859af693cfff31be6c9f2f68efd133de9f54a2f', 'width': 108}, {'height': 121, 'url': 'https://external-preview.redd.it/b2RsbXo5eDJ5MzZmMRaVPCH-YMXWS5H8theQIxqXDZAve_bVCKxOsnpVL7to.png?width=216&crop=smart&format=pjpg&auto=webp&s=48c2ba8d5ac0c3178f75348f94bd168670d6d9ea', 'width': 216}, {'height': 180, 'url': 'https://external-preview.redd.it/b2RsbXo5eDJ5MzZmMRaVPCH-YMXWS5H8theQIxqXDZAve_bVCKxOsnpVL7to.png?width=320&crop=smart&format=pjpg&auto=webp&s=99baa2303a1ede5323cd8c5e08b168af56a5ad9e', 'width': 320}, {'height': 360, 'url': 'https://external-preview.redd.it/b2RsbXo5eDJ5MzZmMRaVPCH-YMXWS5H8theQIxqXDZAve_bVCKxOsnpVL7to.png?width=640&crop=smart&format=pjpg&auto=webp&s=6a3419427aba89c55247d6feae74867e7a1d6ce7', 'width': 640}, {'height': 540, 'url': 'https://external-preview.redd.it/b2RsbXo5eDJ5MzZmMRaVPCH-YMXWS5H8theQIxqXDZAve_bVCKxOsnpVL7to.png?width=960&crop=smart&format=pjpg&auto=webp&s=b7b23ebdda3826f6a78bd945fe559054614b3b03', 'width': 960}, {'height': 607, 'url': 'https://external-preview.redd.it/b2RsbXo5eDJ5MzZmMRaVPCH-YMXWS5H8theQIxqXDZAve_bVCKxOsnpVL7to.png?width=1080&crop=smart&format=pjpg&auto=webp&s=a85a7f90654951f8615c65168ef8752a773fd721', 'width': 1080}], 'source': {'height': 1080, 'url': 'https://external-preview.redd.it/b2RsbXo5eDJ5MzZmMRaVPCH-YMXWS5H8theQIxqXDZAve_bVCKxOsnpVL7to.png?format=pjpg&auto=webp&s=f857d0a00bc291c797aa2cd5b5775c8cfd8d5cfc', 'width': 1920}, 'variants': {}}]} |
||
Google Gemma 3 27B: “I am aware that I am aware” | 1 | [removed] | 2025-06-10T15:07:11 | [deleted] | 1970-01-01T00:00:00 | 0 | {} | 1l814v9 | false | null | t3_1l814v9 | /r/LocalLLaMA/comments/1l814v9/google_gemma_3_27b_i_am_aware_that_i_am_aware/ | false | false | default | 1 | null |
||
Workaround for Windows for CUDA Toolkit download page not working | 4 | Seems like the website is failing with a generic warning from Heroku, however you can download it on Windows from winget using the cmd line:
`winget install -e --id Nvidia.CUDA` | 2025-06-10T15:19:24 | https://www.reddit.com/r/LocalLLaMA/comments/1l81g5i/workaround_for_windows_for_cuda_toolkit_download/ | madcow_bg | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1l81g5i | false | null | t3_1l81g5i | /r/LocalLLaMA/comments/1l81g5i/workaround_for_windows_for_cuda_toolkit_download/ | false | false | self | 4 | null |
You'll own nothing and be happy - 250$ a month for this | 0 | 2025-06-10T15:28:59 | Kooky-Somewhere-2883 | i.redd.it | 1970-01-01T00:00:00 | 0 | {} | 1l81oyl | false | null | t3_1l81oyl | /r/LocalLLaMA/comments/1l81oyl/youll_own_nothing_and_be_happy_250_a_month_for/ | false | false | 0 | {'enabled': True, 'images': [{'id': 'Cgf6U-QU9jXGWkqwYvVcLaEofWCBG-OK8jJsg3kKUMo', 'resolutions': [{'height': 52, 'url': 'https://preview.redd.it/8apwrncqb46f1.png?width=108&crop=smart&auto=webp&s=9e46e4d51ddac75161db23274ca428d464c6e889', 'width': 108}, {'height': 105, 'url': 'https://preview.redd.it/8apwrncqb46f1.png?width=216&crop=smart&auto=webp&s=c53590343cff89c1bc4eb86f24d51912624ca9f0', 'width': 216}, {'height': 156, 'url': 'https://preview.redd.it/8apwrncqb46f1.png?width=320&crop=smart&auto=webp&s=30d9be523db8e9510519ee7ef56c97cda6c38b92', 'width': 320}, {'height': 312, 'url': 'https://preview.redd.it/8apwrncqb46f1.png?width=640&crop=smart&auto=webp&s=db7388b2378e8fcbc4d2023e6ef15f6dfb19231e', 'width': 640}, {'height': 469, 'url': 'https://preview.redd.it/8apwrncqb46f1.png?width=960&crop=smart&auto=webp&s=4cf0e36f7fe28a9ba3819fb6fe8351f8a6945860', 'width': 960}, {'height': 528, 'url': 'https://preview.redd.it/8apwrncqb46f1.png?width=1080&crop=smart&auto=webp&s=2147f7346cfe912e72522fc0383d6138c23d0022', 'width': 1080}], 'source': {'height': 894, 'url': 'https://preview.redd.it/8apwrncqb46f1.png?auto=webp&s=441ca4bfef2a2779179fcb5cbcb8e0a8eb508d14', 'width': 1828}, 'variants': {}}]} |
|||
Real time video generation is finally real | 149 | Introducing Self-Forcing, a new paradigm for training autoregressive diffusion models.
The key to high quality?
Simulate the inference process during training by unrolling transformers with KV caching.
project website: https://self-forcing.github.io
Code/models: https://github.com/guandeh17/Self-Forcing
Source: https://x.com/xunhuang1995/status/1932107954574275059?t=Zh6axAeHtYJ8KRPTeK1T7g&s=19 | 2025-06-10T15:31:23 | https://v.redd.it/l2ydhuibc46f1 | cjsalva | v.redd.it | 1970-01-01T00:00:00 | 0 | {} | 1l81r5n | false | {'reddit_video': {'bitrate_kbps': 2400, 'dash_url': 'https://v.redd.it/l2ydhuibc46f1/DASHPlaylist.mpd?a=1752161497%2CZDEwNDMwYmVjYzFiNzNhODdiOWYyNmVkY2ZlNWQ2NWQ4ZTdjOTFmZDg4NmQ5N2RkNTE0NGYwODJhZGM5ZDk0Yg%3D%3D&v=1&f=sd', 'duration': 9, 'fallback_url': 'https://v.redd.it/l2ydhuibc46f1/DASH_720.mp4?source=fallback', 'has_audio': True, 'height': 592, 'hls_url': 'https://v.redd.it/l2ydhuibc46f1/HLSPlaylist.m3u8?a=1752161497%2COTVlZjBkMTQ3NmYxYzQ4ZmUwZWQxY2IwYWVlOTdlOTVhNTU2NDE5MjBmZWM2ZmM5OWE5YmJhYTY1ODRlMGFmYg%3D%3D&v=1&f=sd', 'is_gif': False, 'scrubber_media_url': 'https://v.redd.it/l2ydhuibc46f1/DASH_96.mp4', 'transcoding_status': 'completed', 'width': 1280}} | t3_1l81r5n | /r/LocalLLaMA/comments/1l81r5n/real_time_video_generation_is_finally_real/ | false | false | 149 | {'enabled': False, 'images': [{'id': 'eTFvYjdramJjNDZmMfyofTFM91phCtF3rAuJHL8Hb7l8ceN-r7OI4BDZRxRZ', 'resolutions': [{'height': 49, 'url': 'https://external-preview.redd.it/eTFvYjdramJjNDZmMfyofTFM91phCtF3rAuJHL8Hb7l8ceN-r7OI4BDZRxRZ.png?width=108&crop=smart&format=pjpg&auto=webp&s=9beab3d2e29dda42ff8e532f526c498fa902d2d9', 'width': 108}, {'height': 99, 'url': 'https://external-preview.redd.it/eTFvYjdramJjNDZmMfyofTFM91phCtF3rAuJHL8Hb7l8ceN-r7OI4BDZRxRZ.png?width=216&crop=smart&format=pjpg&auto=webp&s=3d7831e9c2b4da2f413c22a9f75abff143ad90c1', 'width': 216}, {'height': 147, 'url': 'https://external-preview.redd.it/eTFvYjdramJjNDZmMfyofTFM91phCtF3rAuJHL8Hb7l8ceN-r7OI4BDZRxRZ.png?width=320&crop=smart&format=pjpg&auto=webp&s=d7ee12be1b87454ce91bf1e3daf7846cdee3c2c4', 'width': 320}, {'height': 295, 'url': 'https://external-preview.redd.it/eTFvYjdramJjNDZmMfyofTFM91phCtF3rAuJHL8Hb7l8ceN-r7OI4BDZRxRZ.png?width=640&crop=smart&format=pjpg&auto=webp&s=d5e16a46e9430ce8b2321ee61baec927095743a3', 'width': 640}, {'height': 443, 'url': 'https://external-preview.redd.it/eTFvYjdramJjNDZmMfyofTFM91phCtF3rAuJHL8Hb7l8ceN-r7OI4BDZRxRZ.png?width=960&crop=smart&format=pjpg&auto=webp&s=b5fa6a63c8c1a4c6efe7cca924fb4da2630184a8', 'width': 960}, {'height': 499, 'url': 'https://external-preview.redd.it/eTFvYjdramJjNDZmMfyofTFM91phCtF3rAuJHL8Hb7l8ceN-r7OI4BDZRxRZ.png?width=1080&crop=smart&format=pjpg&auto=webp&s=872234a518a055f186bdd33e0ea015b1f38d9b94', 'width': 1080}], 'source': {'height': 499, 'url': 'https://external-preview.redd.it/eTFvYjdramJjNDZmMfyofTFM91phCtF3rAuJHL8Hb7l8ceN-r7OI4BDZRxRZ.png?format=pjpg&auto=webp&s=4a31767508515339b7156ed0c6f5e7d3c779f1e1', 'width': 1080}, 'variants': {}}]} |
|
Alternatives to a Mac Studio M3 Ultra? | 6 | Giving that VRAM is key to be able to use big LLMs comfortably, I wonder if there are alternatives to the new Mac Studios with 256/512GB of unified memory. You lose CUDA support, yes, but afaik there are no real way to get that kind of vram/throughput in a custom PC, and you are limited by the amount of VRAM in your GPU (32GB in the RTX 5090 is nice, but a little too small for llama/deepseek/qwen on their bigger, less quantized versions.
I wonder also if running those big models is really not that much different from using quantized versions on a more affordable machine (maybe again a mac studio with 96GB of unified memory?
I'm looking for a good compromise here as I'd like to be able to experiment and learn with these models and be able to take advantage of RAG to enable real time search too. | 2025-06-10T15:31:28 | https://www.reddit.com/r/LocalLLaMA/comments/1l81r8e/alternatives_to_a_mac_studio_m3_ultra/ | javipas | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1l81r8e | false | null | t3_1l81r8e | /r/LocalLLaMA/comments/1l81r8e/alternatives_to_a_mac_studio_m3_ultra/ | false | false | self | 6 | null |
I released my pdf translation tool | 1 | [removed] | 2025-06-10T15:51:57 | https://www.reddit.com/r/LocalLLaMA/comments/1l82a1t/i_released_my_pdf_translation_tool/ | smnk2013 | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1l82a1t | false | null | t3_1l82a1t | /r/LocalLLaMA/comments/1l82a1t/i_released_my_pdf_translation_tool/ | false | false | self | 1 | {'enabled': False, 'images': [{'id': 'Tnj356A_E-cyBbc4WZ_XbZu3vhH9F7Fzlu3apqT-oDg', 'resolutions': [{'height': 54, 'url': 'https://external-preview.redd.it/s3vXzYMCbVJ7q8Husf1xTOHm1woUqIrAUd5XCB2TWl4.jpg?width=108&crop=smart&auto=webp&s=ce418cbcccdc6907b5a88521478d2f57164b81bb', 'width': 108}, {'height': 108, 'url': 'https://external-preview.redd.it/s3vXzYMCbVJ7q8Husf1xTOHm1woUqIrAUd5XCB2TWl4.jpg?width=216&crop=smart&auto=webp&s=c16bb04ff7257875ce1203840a0518ad848a198f', 'width': 216}, {'height': 160, 'url': 'https://external-preview.redd.it/s3vXzYMCbVJ7q8Husf1xTOHm1woUqIrAUd5XCB2TWl4.jpg?width=320&crop=smart&auto=webp&s=789e2a1ce0e820da98866db2b10735c852ccecf1', 'width': 320}, {'height': 320, 'url': 'https://external-preview.redd.it/s3vXzYMCbVJ7q8Husf1xTOHm1woUqIrAUd5XCB2TWl4.jpg?width=640&crop=smart&auto=webp&s=5799b8a365f090165ef4b5529faf2cdb7afe2019', 'width': 640}, {'height': 480, 'url': 'https://external-preview.redd.it/s3vXzYMCbVJ7q8Husf1xTOHm1woUqIrAUd5XCB2TWl4.jpg?width=960&crop=smart&auto=webp&s=97676c55bf4e0c7f6ba341fbe9746cfea7ecd865', 'width': 960}, {'height': 540, 'url': 'https://external-preview.redd.it/s3vXzYMCbVJ7q8Husf1xTOHm1woUqIrAUd5XCB2TWl4.jpg?width=1080&crop=smart&auto=webp&s=112f02640e50ab45e98305d1e80d3a46be8938dd', 'width': 1080}], 'source': {'height': 600, 'url': 'https://external-preview.redd.it/s3vXzYMCbVJ7q8Husf1xTOHm1woUqIrAUd5XCB2TWl4.jpg?auto=webp&s=a38a84ac79a89c23d7d380b365df45fae8a5ecdd', 'width': 1200}, 'variants': {}}]} |
A new PDF translation tool | 14 | Hey everyone,
So recently I was tasked with translation of a 200-page document from English to Persian, and I did what any sensible man would do and wrote a python tool to automate it using LLMs.
And I was kinda happy with the results, so I decided to release it on GitHub.
It works by first performing OCR on the PDF (currently only Mistral web) and then sends each page to your LLM of choice with a system prompt and saves the results. The API URL can be customized and local LLMs can be used.
Let me know what you think.
Here is the GitHub link: [https://github.com/smahdink/LLMTranslate](https://github.com/smahdink/LLMTranslate) | 2025-06-10T15:56:07 | https://www.reddit.com/r/LocalLLaMA/comments/1l82ds8/a_new_pdf_translation_tool/ | smnk2013 | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1l82ds8 | false | null | t3_1l82ds8 | /r/LocalLLaMA/comments/1l82ds8/a_new_pdf_translation_tool/ | false | false | self | 14 | {'enabled': False, 'images': [{'id': 'Tnj356A_E-cyBbc4WZ_XbZu3vhH9F7Fzlu3apqT-oDg', 'resolutions': [{'height': 54, 'url': 'https://external-preview.redd.it/s3vXzYMCbVJ7q8Husf1xTOHm1woUqIrAUd5XCB2TWl4.jpg?width=108&crop=smart&auto=webp&s=ce418cbcccdc6907b5a88521478d2f57164b81bb', 'width': 108}, {'height': 108, 'url': 'https://external-preview.redd.it/s3vXzYMCbVJ7q8Husf1xTOHm1woUqIrAUd5XCB2TWl4.jpg?width=216&crop=smart&auto=webp&s=c16bb04ff7257875ce1203840a0518ad848a198f', 'width': 216}, {'height': 160, 'url': 'https://external-preview.redd.it/s3vXzYMCbVJ7q8Husf1xTOHm1woUqIrAUd5XCB2TWl4.jpg?width=320&crop=smart&auto=webp&s=789e2a1ce0e820da98866db2b10735c852ccecf1', 'width': 320}, {'height': 320, 'url': 'https://external-preview.redd.it/s3vXzYMCbVJ7q8Husf1xTOHm1woUqIrAUd5XCB2TWl4.jpg?width=640&crop=smart&auto=webp&s=5799b8a365f090165ef4b5529faf2cdb7afe2019', 'width': 640}, {'height': 480, 'url': 'https://external-preview.redd.it/s3vXzYMCbVJ7q8Husf1xTOHm1woUqIrAUd5XCB2TWl4.jpg?width=960&crop=smart&auto=webp&s=97676c55bf4e0c7f6ba341fbe9746cfea7ecd865', 'width': 960}, {'height': 540, 'url': 'https://external-preview.redd.it/s3vXzYMCbVJ7q8Husf1xTOHm1woUqIrAUd5XCB2TWl4.jpg?width=1080&crop=smart&auto=webp&s=112f02640e50ab45e98305d1e80d3a46be8938dd', 'width': 1080}], 'source': {'height': 600, 'url': 'https://external-preview.redd.it/s3vXzYMCbVJ7q8Husf1xTOHm1woUqIrAUd5XCB2TWl4.jpg?auto=webp&s=a38a84ac79a89c23d7d380b365df45fae8a5ecdd', 'width': 1200}, 'variants': {}}]} |
Google Gemma 3 27B: “I am aware that I am aware” | 1 | [removed] | 2025-06-10T15:56:27 | [deleted] | 1970-01-01T00:00:00 | 0 | {} | 1l82e3p | false | null | t3_1l82e3p | /r/LocalLLaMA/comments/1l82e3p/google_gemma_3_27b_i_am_aware_that_i_am_aware/ | false | false | default | 1 | null |
||
Foundation Model Recommendation | 1 | [removed] | 2025-06-10T16:09:12 | https://www.reddit.com/r/LocalLLaMA/comments/1l82pt7/foundation_model_recommendation/ | GunsN-Roses | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1l82pt7 | false | null | t3_1l82pt7 | /r/LocalLLaMA/comments/1l82pt7/foundation_model_recommendation/ | false | false | self | 1 | null |
Foundation Model Recommendation | 1 | [removed] | 2025-06-10T16:11:51 | https://www.reddit.com/r/LocalLLaMA/comments/1l82sa1/foundation_model_recommendation/ | GunsN-Roses | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1l82sa1 | false | null | t3_1l82sa1 | /r/LocalLLaMA/comments/1l82sa1/foundation_model_recommendation/ | false | false | self | 1 | null |
Open-Source Base Model Recommendation for Medical Q&A? | 1 | [removed] | 2025-06-10T16:13:18 | https://www.reddit.com/r/LocalLLaMA/comments/1l82tm7/opensource_base_model_recommendation_for_medical/ | GunsN-Roses | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1l82tm7 | false | null | t3_1l82tm7 | /r/LocalLLaMA/comments/1l82tm7/opensource_base_model_recommendation_for_medical/ | false | false | self | 1 | null |
I built an autonomous AI artist using Llama 2 that creates art based on emotions, dreams, and music | 1 | [removed] | 2025-06-10T16:18:42 | https://www.youtube.com/@elijahsylar/live | maxximus1995 | youtube.com | 1970-01-01T00:00:00 | 0 | {} | 1l82yld | false | null | t3_1l82yld | /r/LocalLLaMA/comments/1l82yld/i_built_an_autonomous_ai_artist_using_llama_2/ | false | false | default | 1 | null |
Finished extracting everything from the game, separated NSFW and SFW + tried converting Vol 0 to JSON, looking for your feedback! | 0 | Hey everyone,
Just wanted to share where I’m at with extracting data from the game. I’ve finished pulling everything out and neatly separated NSFW and SFW content.
Each character has their own file now, with separate NSFW files for each one—kept everything organized.
Before I spend time converting all files to JSON, I decided to test it out on Vol 0 first and get your thoughts.
Would you recommend I continue converting the rest? Any tips or feedback on the formatting or organization?
I’m open to all criticism—honest opinions only—so I can improve this project.
[https://drive.google.com/file/d/1KP4zwo0f5\_5RZ6YjooyS7TJy10ST8U-1/view?usp=sharing](https://drive.google.com/file/d/1KP4zwo0f5_5RZ6YjooyS7TJy10ST8U-1/view?usp=sharing) | 2025-06-10T16:30:41 | https://www.reddit.com/r/LocalLLaMA/comments/1l839is/finished_extracting_everything_from_the_game/ | Akowmako | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1l839is | false | null | t3_1l839is | /r/LocalLLaMA/comments/1l839is/finished_extracting_everything_from_the_game/ | false | false | nsfw | 0 | null |
Open-source version of Codex / Jules / Background Agents | 1 | [removed] | 2025-06-10T16:37:46 | https://v.redd.it/4tvcn4u1o46f1 | Mango__323521 | v.redd.it | 1970-01-01T00:00:00 | 0 | {} | 1l83fya | false | {'reddit_video': {'bitrate_kbps': 5000, 'dash_url': 'https://v.redd.it/4tvcn4u1o46f1/DASHPlaylist.mpd?a=1752165480%2CYzBhZGE0YjQ4ZDhhM2I1MzBkNjNhYzhmMmNlY2I1YjZhZGFiNjhhYTI1Y2UxNTBiYjBiMTNiYzgzNDI3NTMxMQ%3D%3D&v=1&f=sd', 'duration': 18, 'fallback_url': 'https://v.redd.it/4tvcn4u1o46f1/DASH_1080.mp4?source=fallback', 'has_audio': False, 'height': 1080, 'hls_url': 'https://v.redd.it/4tvcn4u1o46f1/HLSPlaylist.m3u8?a=1752165480%2CMWM4NWIwOTJiYTI5YTIyOGVkNGJiOGYxNDU3ZWQ0MGE0NDU1MmY0NDE2OWZjNmQ2MGVlOTA5NDllYWUwNzM3Yw%3D%3D&v=1&f=sd', 'is_gif': False, 'scrubber_media_url': 'https://v.redd.it/4tvcn4u1o46f1/DASH_96.mp4', 'transcoding_status': 'completed', 'width': 1920}} | t3_1l83fya | /r/LocalLLaMA/comments/1l83fya/opensource_version_of_codex_jules_background/ | false | false | 1 | {'enabled': False, 'images': [{'id': 'NWI0M2g0dTFvNDZmMTPQWKXD0Azxza0G9PcOC7eucsbUYRmny7JcpCMXiVPK', 'resolutions': [{'height': 60, 'url': 'https://external-preview.redd.it/NWI0M2g0dTFvNDZmMTPQWKXD0Azxza0G9PcOC7eucsbUYRmny7JcpCMXiVPK.png?width=108&crop=smart&format=pjpg&auto=webp&s=a84f040b336cdc6d77cb9912b18864cac3fa4a05', 'width': 108}, {'height': 121, 'url': 'https://external-preview.redd.it/NWI0M2g0dTFvNDZmMTPQWKXD0Azxza0G9PcOC7eucsbUYRmny7JcpCMXiVPK.png?width=216&crop=smart&format=pjpg&auto=webp&s=4e5c4ca19ef13895037411de0c6de6510f4c46ff', 'width': 216}, {'height': 180, 'url': 'https://external-preview.redd.it/NWI0M2g0dTFvNDZmMTPQWKXD0Azxza0G9PcOC7eucsbUYRmny7JcpCMXiVPK.png?width=320&crop=smart&format=pjpg&auto=webp&s=1e6b680926c74e6309ddcec48836494d8c02349d', 'width': 320}, {'height': 360, 'url': 'https://external-preview.redd.it/NWI0M2g0dTFvNDZmMTPQWKXD0Azxza0G9PcOC7eucsbUYRmny7JcpCMXiVPK.png?width=640&crop=smart&format=pjpg&auto=webp&s=019219e41c66f7c6afd36deb7fe1198764fa4b74', 'width': 640}, {'height': 540, 'url': 'https://external-preview.redd.it/NWI0M2g0dTFvNDZmMTPQWKXD0Azxza0G9PcOC7eucsbUYRmny7JcpCMXiVPK.png?width=960&crop=smart&format=pjpg&auto=webp&s=76a6400868657154817cebb3c82f800d7f43e909', 'width': 960}, {'height': 607, 'url': 'https://external-preview.redd.it/NWI0M2g0dTFvNDZmMTPQWKXD0Azxza0G9PcOC7eucsbUYRmny7JcpCMXiVPK.png?width=1080&crop=smart&format=pjpg&auto=webp&s=38d9e86217634aaa2ff0f4e774ceb0085c4542ec', 'width': 1080}], 'source': {'height': 1080, 'url': 'https://external-preview.redd.it/NWI0M2g0dTFvNDZmMTPQWKXD0Azxza0G9PcOC7eucsbUYRmny7JcpCMXiVPK.png?format=pjpg&auto=webp&s=c8a21c8fa88f396cadb8fd78923e61112e8cf12a', 'width': 1920}, 'variants': {}}]} |
|
Real head scratcher. | 0 | I know this is a rabbit hole and someone may have already answered this but what is with model hallucinations? Like how do they get so deep and descriptive. Every time I’ve worked with tiny llama early on it swears it’s an intern or works with a team, or runs some kind of business. It will literally go deep. Deep into detail and I’ve always wondered where do these details come from. Where does the base to the “plot” come from? Just always wondered. | 2025-06-10T17:05:11 | https://www.reddit.com/r/LocalLLaMA/comments/1l845p4/real_head_scratcher/ | XDAWONDER | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1l845p4 | false | null | t3_1l845p4 | /r/LocalLLaMA/comments/1l845p4/real_head_scratcher/ | false | false | self | 0 | null |
AI generates real-time visuals from dreams + music using quantum superposition | 1 | [removed] | 2025-06-10T17:09:08 | https://youtube.com/live/1au4E90nmAk?feature=share | maxximus1995 | youtube.com | 1970-01-01T00:00:00 | 0 | {} | 1l849bu | false | null | t3_1l849bu | /r/LocalLLaMA/comments/1l849bu/ai_generates_realtime_visuals_from_dreams_music/ | false | false | default | 1 | null |
Guide: Building an Autonomous AI Artist with Llama 2 - Pattern Generation, Dreams, and Creative Decision-Making | 0 | Here's a comprehensive guide on implementing an autonomous creative AI using llama-cpp-python. Refactored the code for easier use by others (Github link is on my profile).
# Overview
This guide shows how to build an AI that makes autonomous creative decisions using Llama 2 7B. The system generates visual patterns, "dreams" for inspiration, and makes independent choices about its creative process.
# Technical Stack
**Model**: Llama 2 7B Chat (Q4\_K\_M quantization)
**Inference**: llama-cpp-python with GPU acceleration
**Memory**: ChromaDB for vector storage
**Visualization**: Tkinter (yes, really - achieves 60fps!)
**Audio**: librosa for real-time music analysis
# 1. Model Configuration
# Optimal Llama Setup
Initialize with these parameters for best performance:
model\_path: ./models/llama-2-7b-chat.Q4\_K\_M.gguf
n\_gpu\_layers: -1 (use all GPU layers)
n\_ctx: 1024 (context window)
n\_batch: 256 (batch size for prompt eval)
n\_threads: os.cpu\_count() // 2
chat\_format: llama-2
seed: 42 (for reproducibility)
f16\_kv: True (F16 key/value cache)
use\_mmap: True (memory mapping)
use\_mlock: False (don't lock memory)
low\_vram: True (VRAM optimization)
# Key Optimizations
**Q4\_K\_M quantization**: Best quality/performance ratio
**low\_vram=True**: Crucial for consumer GPUs
**n\_threads**: Don't use all cores - leave room for rendering
# 2. Autonomous Decision Architecture
The system uses a 12-dimensional state vector that maps to creative decisions:
**State Dimensions**: valence, arousal, creativity, curiosity, focus, confusion, satisfaction, anticipation, nostalgia, wonder, contemplation, dominance
**Decision Triggers**:
* creativity < 0.4 → request music inspiration
* arousal < 0.3 → initiate dream cycle
* pattern\_fitness < 0.6 → evolve patterns
* stagnation > 50 iterations → request stimulus
# LLM Integration for Creative Decisions
The Llama model generates responses based on internal state, not commands:
**System Prompt Engineering**:
"You are Aurora, an independent AI artist who creates visual patterns based on YOUR OWN artistic vision. You draw inspiration from conversations but don't take commands. Be concise - respond in 1-3 short sentences."
**Key Insight**: Short system prompts with clear autonomy framing produce better results than lengthy instructions.
# 3. Memory System Implementation
# ChromaDB for Persistent Memory
**Collections**:
* conversations (with emotional context extraction)
* dreams (weighted by sleep phase)
* artistic\_inspirations (not user preferences)
* pattern\_history (DNA storage for exact recreation)
**Embedding Strategy**: Use sentence-transformers/all-MiniLM-L6-v2 for efficiency
# Memory Query Optimization
Limit context injection to 3-5 most relevant memories. More context degrades Llama's response quality and increases latency.
# 4. Real-time Response Optimization
# Achieving <1s Response Times
**Minimize Token Generation**:
* max\_tokens: 100-150 (users don't read long responses)
* temperature: 0.7 (balance creativity/coherence)
* stop sequences: \["Human:", "User:", "\\n\\n\\n"\]
**Background Processing**:
All non-critical operations (memory storage, logging, state updates) run in separate threads after response delivery.
# 5. Pattern Generation with LLM Context
# Emotional State → Visual Parameters
The system maps emotional dimensions to 100+ visual parameters:
pattern\_complexity = 0.3 + 0.7 \* (curiosity + creativity + focus) / 3
chaos\_level = confusion + 0.3 \* (1 - focus)
color\_saturation = 0.4 + 0.6 \* (valence + 1) / 2
# Dream Cycles for Creative Processing
**Sleep Phases**: light\_sleep → deep\_sleep → rem\_sleep → light\_sleep
**Duration**: 2-3 hours (scaled for demonstration)
**LLM Role**: Generates dream content based on recent memories
During REM sleep, the model generates vivid creative narratives that influence pattern generation upon waking.
# 6. Performance Considerations
# GPU Memory Management
**8GB VRAM Setup**:
* Model: \~4GB with Q4\_K\_M
* Context cache: \~1GB
* Overhead: \~1GB
* Leaves 2GB for other processes
**16GB+ VRAM**: Can use Q5\_K\_M or Q6\_K for better quality
# CPU Fallback
The system works on CPU-only but with significant latency:
* Response time: 5-10s vs <1s with GPU
* Set n\_gpu\_layers=0 for pure CPU inference
# 7. Interesting Discoveries
# Emergent Behaviors
1. **Music Preferences**: The AI consistently requests specific genres based on creative state
2. **Dream Coherence**: REM dreams show narrative consistency across sessions
3. **Pattern Evolution**: Certain pattern "species" dominate over time based on fitness
# Prompt Engineering Tips
**For Autonomy**: Frame the AI as having internal experiences rather than simulating them
**For Creativity**: Use emotional language in system prompts
**For Consistency**: Maintain conversation history in memory, not context
# Implementation Guide
Full code structure available at: [github.com/elijahsylar/Aurora-Autonomous-AI-Artist](http://github.com/elijahsylar/Aurora-Autonomous-AI-Artist)
Key directories:
aurora/ - Main implementation
aurora/ai/ - LLM integration
aurora/patterns/ - Visual generation
aurora/memory/ - ChromaDB setup
# Hardware Requirements
**Minimum**: 8GB RAM, 6GB VRAM, 4-core CPU
**Recommended**: 16GB RAM, 8GB+ VRAM, 8-core CPU
**Tested on**: RTX 3060 12GB, Ryzen 5 5600X
# Common Issues and Solutions
**High VRAM usage**: Reduce n\_ctx to 512
**Slow responses**: Decrease max\_tokens, increase n\_batch
**Repetitive outputs**: Adjust repeat\_penalty to 1.2-1.3
**ChromaDB errors**: Delete aurora\_memory/ folder and restart
# Future Improvements
1. Implement LoRA for style-specific responses
2. Add speculative decoding for faster inference
3. Experiment with Mixtral for better creative reasoning
4. Implement streaming for perceived faster responses
Questions or improvements? The codebase is actively maintained and PRs are welcome! | 2025-06-10T17:18:27 | https://www.reddit.com/r/LocalLLaMA/comments/1l84i3u/guide_building_an_autonomous_ai_artist_with_llama/ | maxximus1995 | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1l84i3u | false | null | t3_1l84i3u | /r/LocalLLaMA/comments/1l84i3u/guide_building_an_autonomous_ai_artist_with_llama/ | false | false | self | 0 | {'enabled': False, 'images': [{'id': 'NQ7X1CyipU6MmsypWhAtuJH85u-UcLjAtcJLCidMmc4', 'resolutions': [{'height': 54, 'url': 'https://external-preview.redd.it/tfxuOupLg7m4-oP4NKTcbIRqfCj2VxtnItyfnu4fFyI.jpg?width=108&crop=smart&auto=webp&s=e95e314ee0874cde228f5a2d108e3182237959d8', 'width': 108}, {'height': 108, 'url': 'https://external-preview.redd.it/tfxuOupLg7m4-oP4NKTcbIRqfCj2VxtnItyfnu4fFyI.jpg?width=216&crop=smart&auto=webp&s=f2f10b6af18a465874a4144b26c08542d4b29eee', 'width': 216}, {'height': 160, 'url': 'https://external-preview.redd.it/tfxuOupLg7m4-oP4NKTcbIRqfCj2VxtnItyfnu4fFyI.jpg?width=320&crop=smart&auto=webp&s=22b7adb62917715c19d0baed39832aac321af943', 'width': 320}, {'height': 320, 'url': 'https://external-preview.redd.it/tfxuOupLg7m4-oP4NKTcbIRqfCj2VxtnItyfnu4fFyI.jpg?width=640&crop=smart&auto=webp&s=60735f968dab85947a52a17464ede0923a026d70', 'width': 640}, {'height': 480, 'url': 'https://external-preview.redd.it/tfxuOupLg7m4-oP4NKTcbIRqfCj2VxtnItyfnu4fFyI.jpg?width=960&crop=smart&auto=webp&s=43e4539f1a7a75a7eb236dc68b23e07f647aaa1e', 'width': 960}, {'height': 540, 'url': 'https://external-preview.redd.it/tfxuOupLg7m4-oP4NKTcbIRqfCj2VxtnItyfnu4fFyI.jpg?width=1080&crop=smart&auto=webp&s=129a81fb92069f906a9c8ec40145d36fad1d315b', 'width': 1080}], 'source': {'height': 600, 'url': 'https://external-preview.redd.it/tfxuOupLg7m4-oP4NKTcbIRqfCj2VxtnItyfnu4fFyI.jpg?auto=webp&s=4cb2b9c7fc542a3a42a2fd2146776165f87cf218', 'width': 1200}, 'variants': {}}]} |
Teams Building AI Agents for Enterprise Use | 1 | [removed] | 2025-06-10T17:26:37 | https://www.reddit.com/r/LocalLLaMA/comments/1l84pr9/teams_building_ai_agents_for_enterprise_use/ | rahat008 | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1l84pr9 | false | null | t3_1l84pr9 | /r/LocalLLaMA/comments/1l84pr9/teams_building_ai_agents_for_enterprise_use/ | false | false | self | 1 | null |
When Qwen Decides It's Time for a Language Lesson | 1 | [removed] | 2025-06-10T17:43:00 | Purple_Singer3078 | i.redd.it | 1970-01-01T00:00:00 | 0 | {} | 1l855ff | false | null | t3_1l855ff | /r/LocalLLaMA/comments/1l855ff/when_qwen_decides_its_time_for_a_language_lesson/ | false | false | 1 | {'enabled': True, 'images': [{'id': '1q-BYFCIdqOLIqkxLiBjjnR-fsM35tP-LhQDtzXBk70', 'resolutions': [{'height': 120, 'url': 'https://preview.redd.it/h0ukee0gx46f1.png?width=108&crop=smart&auto=webp&s=7e0dc4678f8869f69337d3607ff2c015cb5ef93c', 'width': 108}, {'height': 241, 'url': 'https://preview.redd.it/h0ukee0gx46f1.png?width=216&crop=smart&auto=webp&s=ad0e10e939431d631dc01a3d23b326180e850c80', 'width': 216}, {'height': 358, 'url': 'https://preview.redd.it/h0ukee0gx46f1.png?width=320&crop=smart&auto=webp&s=3849091269e9093383bbd7c67c00db692c9b8650', 'width': 320}], 'source': {'height': 591, 'url': 'https://preview.redd.it/h0ukee0gx46f1.png?auto=webp&s=f33bbd66084f126243c25ce9d27ba57a19cf5d3c', 'width': 528}, 'variants': {}}]} |
||
Inference engines with adjustable context size on Mac | 6 | mlx_lm doesn’t seem to support increasing the context size. Maybe I’m just missing it?
What is a good alternative for Python on Mac? | 2025-06-10T18:05:58 | https://www.reddit.com/r/LocalLLaMA/comments/1l85rlj/inference_engines_with_adjustable_context_size_on/ | Puzzleheaded-Fee5917 | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1l85rlj | false | null | t3_1l85rlj | /r/LocalLLaMA/comments/1l85rlj/inference_engines_with_adjustable_context_size_on/ | false | false | self | 6 | null |
Attention everyone here | 1 | [removed] | 2025-06-10T18:44:43 | https://www.reddit.com/r/LocalLLaMA/comments/1l86s5q/attention_everyone_here/ | arhaanpro | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1l86s5q | false | null | t3_1l86s5q | /r/LocalLLaMA/comments/1l86s5q/attention_everyone_here/ | false | false | self | 1 | {'enabled': False, 'images': [{'id': 'MxSQlmxsqZADMaQKQa8AsR5nvUJHtT6d3Y_u5x8FXMg', 'resolutions': [{'height': 60, 'url': 'https://external-preview.redd.it/yq53jkXKq-F9zv3Pn9s9044KcSnuYS2VY3QD923BnMo.jpg?width=108&crop=smart&auto=webp&s=d6b82ef7c1beb35926d799d657e1bb513c461daf', 'width': 108}, {'height': 121, 'url': 'https://external-preview.redd.it/yq53jkXKq-F9zv3Pn9s9044KcSnuYS2VY3QD923BnMo.jpg?width=216&crop=smart&auto=webp&s=4e72dbe1a079bf24c2bcca7251bae94b6229c16b', 'width': 216}, {'height': 180, 'url': 'https://external-preview.redd.it/yq53jkXKq-F9zv3Pn9s9044KcSnuYS2VY3QD923BnMo.jpg?width=320&crop=smart&auto=webp&s=372dc934015c976c5cb121cfac0edab2d606044a', 'width': 320}, {'height': 360, 'url': 'https://external-preview.redd.it/yq53jkXKq-F9zv3Pn9s9044KcSnuYS2VY3QD923BnMo.jpg?width=640&crop=smart&auto=webp&s=191e7e0cb2d7008a53c3111625a2d75155320064', 'width': 640}, {'height': 540, 'url': 'https://external-preview.redd.it/yq53jkXKq-F9zv3Pn9s9044KcSnuYS2VY3QD923BnMo.jpg?width=960&crop=smart&auto=webp&s=2617ef9b6f2b0057da4c23f5fab76526e898ebdd', 'width': 960}, {'height': 607, 'url': 'https://external-preview.redd.it/yq53jkXKq-F9zv3Pn9s9044KcSnuYS2VY3QD923BnMo.jpg?width=1080&crop=smart&auto=webp&s=f7130cfbb3c12d96c4608c9b5389c5cd136296e9', 'width': 1080}], 'source': {'height': 900, 'url': 'https://external-preview.redd.it/yq53jkXKq-F9zv3Pn9s9044KcSnuYS2VY3QD923BnMo.jpg?auto=webp&s=cdb1a0b55d6ac582ec66bb83365a9ae1f86d849c', 'width': 1600}, 'variants': {}}]} |
Fully local animated characters on your phone | 30 | Hey! I would like to share something I've been working on over the past weeks: take your AI characters to the next level!
Everything runs locally on a consumer phone (video shows phone in airplane mode). Supports both voice and text chat.
Tech stack:
* Hardware: S23 Ultra (Snapdragon Gen 2)
* Model: L3-Rhaenys-8B (CPU inference)
* Speech-to-text: Kroko-ASR
* Text-to-speech: Bixby (Local voice) (from Samsung Galaxy)
* Sentiment detection: RoBERTa (sentiment links to dynamic character expressions)
* Supports any Live2D models
* Animation reacts in real-time to phone gyroscope
* Lip sync to phone audio output
Fully customisable: bring your own LLM models, create your own character, import your own Live2D models, link your own expressions. Tutorial here: [https://www.layla-network.ai/post/how-to-import-live2d-models-in-layla](https://www.layla-network.ai/post/how-to-import-live2d-models-in-layla) | 2025-06-10T18:44:50 | https://v.redd.it/p5nlsg02856f1 | Tasty-Lobster-8915 | v.redd.it | 1970-01-01T00:00:00 | 0 | {} | 1l86sa1 | false | {'reddit_video': {'bitrate_kbps': 5000, 'dash_url': 'https://v.redd.it/p5nlsg02856f1/DASHPlaylist.mpd?a=1752173133%2COTlhYWQ4ZDhiMDBkZjRmMjVhM2Y2YjFjMzQ0MjNiNTIxMTA2YjQwZTQxYjAyNmI3YTZmZmMwZTNmYjQ4Njk5YQ%3D%3D&v=1&f=sd', 'duration': 74, 'fallback_url': 'https://v.redd.it/p5nlsg02856f1/DASH_1080.mp4?source=fallback', 'has_audio': True, 'height': 1920, 'hls_url': 'https://v.redd.it/p5nlsg02856f1/HLSPlaylist.m3u8?a=1752173133%2CYWRiZjM3OGQwMDc5ZDcxYWU0OWZkYjRhOGJkMzZlYTZiMTg3ZWRmMjUxOTU5MDZiNzhmYWQ5OTg1NjUyOTVlNQ%3D%3D&v=1&f=sd', 'is_gif': False, 'scrubber_media_url': 'https://v.redd.it/p5nlsg02856f1/DASH_96.mp4', 'transcoding_status': 'completed', 'width': 896}} | t3_1l86sa1 | /r/LocalLLaMA/comments/1l86sa1/fully_local_animated_characters_on_your_phone/ | false | false | 30 | {'enabled': False, 'images': [{'id': 'dHdzb3NpMDI4NTZmMeu_O_0PhnMKT5g93FfyNeGEm2wEDzsZaS2w2XSNVCkB', 'resolutions': [{'height': 216, 'url': 'https://external-preview.redd.it/dHdzb3NpMDI4NTZmMeu_O_0PhnMKT5g93FfyNeGEm2wEDzsZaS2w2XSNVCkB.png?width=108&crop=smart&format=pjpg&auto=webp&s=f4fb227c8682e47954df8202749c512a84b58d56', 'width': 108}, {'height': 432, 'url': 'https://external-preview.redd.it/dHdzb3NpMDI4NTZmMeu_O_0PhnMKT5g93FfyNeGEm2wEDzsZaS2w2XSNVCkB.png?width=216&crop=smart&format=pjpg&auto=webp&s=c09ccca2c896ad3a96b7015839ec85067707c95a', 'width': 216}, {'height': 640, 'url': 'https://external-preview.redd.it/dHdzb3NpMDI4NTZmMeu_O_0PhnMKT5g93FfyNeGEm2wEDzsZaS2w2XSNVCkB.png?width=320&crop=smart&format=pjpg&auto=webp&s=78c12bbc288ada9393ddbcfdaa6159c9933dfd84', 'width': 320}, {'height': 1280, 'url': 'https://external-preview.redd.it/dHdzb3NpMDI4NTZmMeu_O_0PhnMKT5g93FfyNeGEm2wEDzsZaS2w2XSNVCkB.png?width=640&crop=smart&format=pjpg&auto=webp&s=444298886c2d52c5f15ded3154ce8e67c4e96bc6', 'width': 640}, {'height': 1920, 'url': 'https://external-preview.redd.it/dHdzb3NpMDI4NTZmMeu_O_0PhnMKT5g93FfyNeGEm2wEDzsZaS2w2XSNVCkB.png?width=960&crop=smart&format=pjpg&auto=webp&s=f3835963c0048dc329c2d70f4b6db82b823792fa', 'width': 960}, {'height': 2160, 'url': 'https://external-preview.redd.it/dHdzb3NpMDI4NTZmMeu_O_0PhnMKT5g93FfyNeGEm2wEDzsZaS2w2XSNVCkB.png?width=1080&crop=smart&format=pjpg&auto=webp&s=efae252bf1ff6f1b14fe19c16f64213fe544d24c', 'width': 1080}], 'source': {'height': 2316, 'url': 'https://external-preview.redd.it/dHdzb3NpMDI4NTZmMeu_O_0PhnMKT5g93FfyNeGEm2wEDzsZaS2w2XSNVCkB.png?format=pjpg&auto=webp&s=6250c9536b4cd9c5546e32f460accaed9b8c7359', 'width': 1080}, 'variants': {}}]} |
|
Security Tool For Developers Making AI Agent - What Do You Need? | 1 | [removed] | 2025-06-10T18:58:51 | https://www.reddit.com/r/LocalLLaMA/comments/1l87570/security_tool_for_developers_making_ai_agent_what/ | Artistic_Bee_2117 | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1l87570 | false | null | t3_1l87570 | /r/LocalLLaMA/comments/1l87570/security_tool_for_developers_making_ai_agent_what/ | false | false | self | 1 | null |
RoboBrain2.0 7B and 32B - See Better. Think Harder. Do Smarter. | 121 |
RoboBrain 2.0 supports interactive reasoning with long-horizon planning and closed-loop feedback, spatial perception for precise point and bbox prediction from complex instructions, temporal perception for future trajectory estimation, and scene reasoning through real-time structured memory construction and update.
| 2025-06-10T18:59:04 | https://huggingface.co/BAAI/RoboBrain2.0-7B | Mandelaa | huggingface.co | 1970-01-01T00:00:00 | 0 | {} | 1l875e4 | false | null | t3_1l875e4 | /r/LocalLLaMA/comments/1l875e4/robobrain20_7b_and_32b_see_better_think_harder_do/ | false | false | 121 | {'enabled': False, 'images': [{'id': 'GcZNSwJiJS8MiF7jp0hPOtuQtEgnuAXF__1RGijkvq0', 'resolutions': [{'height': 58, 'url': 'https://external-preview.redd.it/GcZNSwJiJS8MiF7jp0hPOtuQtEgnuAXF__1RGijkvq0.png?width=108&crop=smart&auto=webp&s=2554210ef4d92fc91b98377143dde1ade5e5ec41', 'width': 108}, {'height': 116, 'url': 'https://external-preview.redd.it/GcZNSwJiJS8MiF7jp0hPOtuQtEgnuAXF__1RGijkvq0.png?width=216&crop=smart&auto=webp&s=745b316c61f3f99820f91e9aab60d679527271c6', 'width': 216}, {'height': 172, 'url': 'https://external-preview.redd.it/GcZNSwJiJS8MiF7jp0hPOtuQtEgnuAXF__1RGijkvq0.png?width=320&crop=smart&auto=webp&s=8fde2dffb2c28709c4f0f10085abfbcaa8396858', 'width': 320}, {'height': 345, 'url': 'https://external-preview.redd.it/GcZNSwJiJS8MiF7jp0hPOtuQtEgnuAXF__1RGijkvq0.png?width=640&crop=smart&auto=webp&s=6fa30b12dd42cf753d30059fd402ede5655a1a93', 'width': 640}, {'height': 518, 'url': 'https://external-preview.redd.it/GcZNSwJiJS8MiF7jp0hPOtuQtEgnuAXF__1RGijkvq0.png?width=960&crop=smart&auto=webp&s=197f427b5310ed330cda8dcff75c5c9535eb9ed1', 'width': 960}, {'height': 583, 'url': 'https://external-preview.redd.it/GcZNSwJiJS8MiF7jp0hPOtuQtEgnuAXF__1RGijkvq0.png?width=1080&crop=smart&auto=webp&s=adf199c502fd4516e0689e206ff4460bb7712312', 'width': 1080}], 'source': {'height': 648, 'url': 'https://external-preview.redd.it/GcZNSwJiJS8MiF7jp0hPOtuQtEgnuAXF__1RGijkvq0.png?auto=webp&s=db5514c7adfa2475a6ede74376dc9fce19aa58eb', 'width': 1200}, 'variants': {}}]} |
|
Dual gpu for running 20gb+ models | 1 | [removed] | 2025-06-10T19:20:45 | https://www.reddit.com/r/LocalLLaMA/comments/1l87pqm/dual_gpu_for_running_20gb_models/ | No_Nothing1584 | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1l87pqm | false | null | t3_1l87pqm | /r/LocalLLaMA/comments/1l87pqm/dual_gpu_for_running_20gb_models/ | false | false | self | 1 | null |
Ollama: Ollama repo or HF GGUF | 1 | [removed] | 2025-06-10T19:32:47 | https://www.reddit.com/r/LocalLLaMA/comments/1l880ps/ollama_ollama_repo_or_hf_gguf/ | Inside_Assistance_20 | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1l880ps | false | null | t3_1l880ps | /r/LocalLLaMA/comments/1l880ps/ollama_ollama_repo_or_hf_gguf/ | false | false | self | 1 | null |
Best possible AI workstation for ~$400 all-in? | 0 | Hi all -
I have about $400 left on a grant that I would love to use to start up an AI server that I could improve with further grants/personal money. Right now I’m looking at some kind of HP Z640 build with a 2060 super 8GB right around ~$410, but not sure if there’s a better value for the money that I could get now.
The Z640 seems interesting to me because the mobo can fit multiple GPUs, has dual processor capability, and isn’t overwhelmingly expensive. Priorities-wise, upfront cost is more important than scalability which is more important than upfront performance, but I’m hoping to maximize the value on all of three of those measures. I understand I can’t do much right now (hoping for good 7B performance if possible), but down the line I’d love good 70B performance.
Please let me know if anyone has any ideas better than my current plan! | 2025-06-10T19:39:11 | https://www.reddit.com/r/LocalLLaMA/comments/1l886kw/best_possible_ai_workstation_for_400_allin/ | Butterhero_ | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1l886kw | false | null | t3_1l886kw | /r/LocalLLaMA/comments/1l886kw/best_possible_ai_workstation_for_400_allin/ | false | false | self | 0 | null |
[oc] Do open weight reasoning models have an issue with token spamming? | 20 | I performed a quick and dirty experiment (n=1, except deephermes with n=3) where i compared how many tokens different reasoning models require to answer the prompt:
`In a room of 30 people, what's the probability that at least two do not share a birthday?`
This is a slightly misleading prompt that requires some iterations on the CoT to get the correct answer.
Open weight models require significantly more tokens to respond than closed weight reasoning models.
It seems that, generally, open weight models are not trained to limit the CoT very efficiently.
This seems to be a significant omission that somewhat limits the useability of this models for practical tasks.
https://preview.redd.it/pj7iwlx2k56f1.png?width=2379&format=png&auto=webp&s=b7c8c7239e2ca2052791748cb9f9dddfb799eb91
| 2025-06-10T19:42:02 | https://www.reddit.com/r/LocalLLaMA/comments/1l8898q/oc_do_open_weight_reasoning_models_have_an_issue/ | cpldcpu | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1l8898q | false | null | t3_1l8898q | /r/LocalLLaMA/comments/1l8898q/oc_do_open_weight_reasoning_models_have_an_issue/ | false | false | 20 | {'enabled': False, 'images': [{'id': 'GNeWyFToIQL7gN4a57lIF0K1-LL76-7UjTjjhTOdj0I', 'resolutions': [{'height': 44, 'url': 'https://external-preview.redd.it/7gTnvK_MmfZ8sL3JUZZkf8WeqfWkD9OdkUr0vzdOsG0.png?width=108&crop=smart&auto=webp&s=434ce7327aff4f1e6d246421e7b4290531d33460', 'width': 108}, {'height': 88, 'url': 'https://external-preview.redd.it/7gTnvK_MmfZ8sL3JUZZkf8WeqfWkD9OdkUr0vzdOsG0.png?width=216&crop=smart&auto=webp&s=9e13f3407f53911cfb88c2eb24e23bb96dff466f', 'width': 216}, {'height': 131, 'url': 'https://external-preview.redd.it/7gTnvK_MmfZ8sL3JUZZkf8WeqfWkD9OdkUr0vzdOsG0.png?width=320&crop=smart&auto=webp&s=39019b130f8fbb02f8bea45091bd9a27cfef1b81', 'width': 320}, {'height': 263, 'url': 'https://external-preview.redd.it/7gTnvK_MmfZ8sL3JUZZkf8WeqfWkD9OdkUr0vzdOsG0.png?width=640&crop=smart&auto=webp&s=6e319307bbe73d0fb297386d2f876141e32f80bd', 'width': 640}, {'height': 395, 'url': 'https://external-preview.redd.it/7gTnvK_MmfZ8sL3JUZZkf8WeqfWkD9OdkUr0vzdOsG0.png?width=960&crop=smart&auto=webp&s=11ebba5ecdd1b1640ae31167b162ef767f2bae14', 'width': 960}, {'height': 444, 'url': 'https://external-preview.redd.it/7gTnvK_MmfZ8sL3JUZZkf8WeqfWkD9OdkUr0vzdOsG0.png?width=1080&crop=smart&auto=webp&s=2e3ad979b4cbbef986cad3818f52e9927846d864', 'width': 1080}], 'source': {'height': 980, 'url': 'https://external-preview.redd.it/7gTnvK_MmfZ8sL3JUZZkf8WeqfWkD9OdkUr0vzdOsG0.png?auto=webp&s=364f3ceceeb688aa127dcdbcdd0728647ca7fb1a', 'width': 2379}, 'variants': {}}]} |
|
best fine tuned local LLM for Github Copilot Agent specificaly | 1 | What is the best fine tuned local LLMs for Github Copilot Agent specificaly? | 2025-06-10T19:51:54 | https://www.reddit.com/r/LocalLLaMA/comments/1l88i69/best_fine_tuned_local_llm_for_github_copilot/ | solidavocadorock | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1l88i69 | false | null | t3_1l88i69 | /r/LocalLLaMA/comments/1l88i69/best_fine_tuned_local_llm_for_github_copilot/ | false | false | self | 1 | null |
Local LLM (<30Gb) to translate a LaTeX document | 1 | [removed] | 2025-06-10T20:08:11 | https://www.reddit.com/r/LocalLLaMA/comments/1l88xbz/local_llm_30gb_to_translate_a_latex_document/ | tobiasBora | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1l88xbz | false | null | t3_1l88xbz | /r/LocalLLaMA/comments/1l88xbz/local_llm_30gb_to_translate_a_latex_document/ | false | false | self | 1 | null |
GMKtek Strix Halo LLM Review | 25 | [https://www.youtube.com/watch?v=B7GDr-VFuEo](https://www.youtube.com/watch?v=B7GDr-VFuEo)
Interesting video. Even compares it to a base M4 Mac mini with a ton of memory. | 2025-06-10T20:11:38 | https://www.reddit.com/r/LocalLLaMA/comments/1l890kf/gmktek_strix_halo_llm_review/ | Slasher1738 | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1l890kf | false | null | t3_1l890kf | /r/LocalLLaMA/comments/1l890kf/gmktek_strix_halo_llm_review/ | false | false | self | 25 | {'enabled': False, 'images': [{'id': 'ZJGhqTlZfjBWVv7O9WZWFOqMneu3vdzEKt4vvX-2oCU', 'resolutions': [{'height': 81, 'url': 'https://external-preview.redd.it/5vI6ecYmwoaT1rC3tx4wyN4auw4yGiIVcX9YLcwSAzk.jpg?width=108&crop=smart&auto=webp&s=cd73e7516edc1df7c8656e770728d04b4a1a9286', 'width': 108}, {'height': 162, 'url': 'https://external-preview.redd.it/5vI6ecYmwoaT1rC3tx4wyN4auw4yGiIVcX9YLcwSAzk.jpg?width=216&crop=smart&auto=webp&s=305a3fe9b1cd7b0977ec7bf66113f271bba052a1', 'width': 216}, {'height': 240, 'url': 'https://external-preview.redd.it/5vI6ecYmwoaT1rC3tx4wyN4auw4yGiIVcX9YLcwSAzk.jpg?width=320&crop=smart&auto=webp&s=212fb891af236d350886fb6c5d891cb283575719', 'width': 320}], 'source': {'height': 360, 'url': 'https://external-preview.redd.it/5vI6ecYmwoaT1rC3tx4wyN4auw4yGiIVcX9YLcwSAzk.jpg?auto=webp&s=5126f4b6335a30891940350f874ad7d973f6f46f', 'width': 480}, 'variants': {}}]} |
Running LLM on local GPU | 1 | [removed] | 2025-06-10T21:05:38 | https://www.reddit.com/r/LocalLLaMA/comments/1l8ae8i/running_llm_on_local_gpu/ | JJJurix | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1l8ae8i | false | null | t3_1l8ae8i | /r/LocalLLaMA/comments/1l8ae8i/running_llm_on_local_gpu/ | false | false | self | 1 | null |
Has anyone tried to commercialize local LLM based products? What were your learnings? | 0 | What were your challenges, learnings and was there anything that surprised you? What type of customers prefer a local LLM, compared to a turnkey solution like a cloud based provider? Seems like configuring the infra pushes one back in the race, where time to market is everything. | 2025-06-10T21:07:21 | https://www.reddit.com/r/LocalLLaMA/comments/1l8afv1/has_anyone_tried_to_commercialize_local_llm_based/ | __amberluz__ | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1l8afv1 | false | null | t3_1l8afv1 | /r/LocalLLaMA/comments/1l8afv1/has_anyone_tried_to_commercialize_local_llm_based/ | false | false | self | 0 | null |
Running LLM on local GPU | 1 | [removed] | 2025-06-10T21:08:58 | https://www.reddit.com/r/LocalLLaMA/comments/1l8ahaj/running_llm_on_local_gpu/ | JJJurix | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1l8ahaj | false | null | t3_1l8ahaj | /r/LocalLLaMA/comments/1l8ahaj/running_llm_on_local_gpu/ | false | false | default | 1 | null |
Looking for an ai co founder for a 7 figure raising pre seed ai startup | 1 | [removed] | 2025-06-10T21:10:43 | https://www.reddit.com/r/LocalLLaMA/comments/1l8aivj/looking_for_an_ai_co_founder_for_a_7_figure/ | unknownstudentoflife | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1l8aivj | false | null | t3_1l8aivj | /r/LocalLLaMA/comments/1l8aivj/looking_for_an_ai_co_founder_for_a_7_figure/ | false | false | default | 1 | null |
Poetry competition: Opus 4 vs O3 Pro vs Gemini 2.5 Pro Preview | 1 | [removed] | 2025-06-10T21:17:22 | https://www.reddit.com/r/LocalLLaMA/comments/1l8ap02/poetry_competition_opus_4_vs_o3_pro_vs_gemini_25/ | Agile_Builder7710 | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1l8ap02 | false | null | t3_1l8ap02 | /r/LocalLLaMA/comments/1l8ap02/poetry_competition_opus_4_vs_o3_pro_vs_gemini_25/ | false | false | 1 | null |
|
Holo1 by H Company: New $220M AI lab (ex-DeepMind) just open-sourced a web agent (Apache 2.0) | 1 | 2025-06-10T21:28:18 | https://huggingface.co/collections/Hcompany/holo1-683dd1eece7eb077b96d0cbd | themoregames | huggingface.co | 1970-01-01T00:00:00 | 0 | {} | 1l8ays9 | false | null | t3_1l8ays9 | /r/LocalLLaMA/comments/1l8ays9/holo1_by_h_company_new_220m_ai_lab_exdeepmind/ | false | false | 1 | {'enabled': False, 'images': [{'id': 'si1KJ5cCN0bP7J7sh-G-GiBOKclBuGEbgOIdk6LBZPc', 'resolutions': [{'height': 58, 'url': 'https://external-preview.redd.it/vzLV-lHRhEC8oKFrw7z5_4i02RQNSdl0QM4ASrVZzwM.jpg?width=108&crop=smart&auto=webp&s=f229d143a6c582f7381b333e117e9141111480d5', 'width': 108}, {'height': 116, 'url': 'https://external-preview.redd.it/vzLV-lHRhEC8oKFrw7z5_4i02RQNSdl0QM4ASrVZzwM.jpg?width=216&crop=smart&auto=webp&s=2a96897848036df2222d47d4103da894ba6f2f3d', 'width': 216}, {'height': 172, 'url': 'https://external-preview.redd.it/vzLV-lHRhEC8oKFrw7z5_4i02RQNSdl0QM4ASrVZzwM.jpg?width=320&crop=smart&auto=webp&s=56f79cb37e629f95c488398d769eceb6f8144f87', 'width': 320}, {'height': 345, 'url': 'https://external-preview.redd.it/vzLV-lHRhEC8oKFrw7z5_4i02RQNSdl0QM4ASrVZzwM.jpg?width=640&crop=smart&auto=webp&s=90f1b525144dd8760a209a51d009e3386c0cbb93', 'width': 640}, {'height': 518, 'url': 'https://external-preview.redd.it/vzLV-lHRhEC8oKFrw7z5_4i02RQNSdl0QM4ASrVZzwM.jpg?width=960&crop=smart&auto=webp&s=f658e41759510fc3ade84ac39c9472905fc4a2cd', 'width': 960}, {'height': 583, 'url': 'https://external-preview.redd.it/vzLV-lHRhEC8oKFrw7z5_4i02RQNSdl0QM4ASrVZzwM.jpg?width=1080&crop=smart&auto=webp&s=f90d4ca62c6b6da513e520165d495074895cb2a6', 'width': 1080}], 'source': {'height': 648, 'url': 'https://external-preview.redd.it/vzLV-lHRhEC8oKFrw7z5_4i02RQNSdl0QM4ASrVZzwM.jpg?auto=webp&s=feb424154c94dbf0f7b2bf3a536c6ec737a66b99', 'width': 1200}, 'variants': {}}]} |
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Augmentoolkit Dataset with Unsloth - Which File to Use? | 2 | Hi everyone,
I recently created a dataset using Augmentoolkit, and the process generated several files: `master_list.jsonl`, `simplified_data_no_rag.jsonl`, `simplified_data_rag.jsonl`, and `plain_qa_list.jsonl`.
I'm a little unsure which of these files is best suited for use with Unsloth, and I'm hoping someone can point me in the right direction. Does anyone have a guide, tutorial, or even just their experience using an Augmentoolkit dataset with Unsloth? Any links or advice would be greatly appreciated! | 2025-06-10T21:34:02 | https://www.reddit.com/r/LocalLLaMA/comments/1l8b3ri/augmentoolkit_dataset_with_unsloth_which_file_to/ | Empty_Object_9299 | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1l8b3ri | false | null | t3_1l8b3ri | /r/LocalLLaMA/comments/1l8b3ri/augmentoolkit_dataset_with_unsloth_which_file_to/ | false | false | self | 2 | null |
Just got these in the mail! | 1 | [removed] | 2025-06-10T21:39:19 | heyitsapenguin | i.redd.it | 1970-01-01T00:00:00 | 0 | {} | 1l8b8dd | false | null | t3_1l8b8dd | /r/LocalLLaMA/comments/1l8b8dd/just_got_these_in_the_mail/ | false | false | 1 | {'enabled': True, 'images': [{'id': 'ohiKse-uUI7fKw5fNVzwtT2SNKQ68MYGBSGiQ9jPwvc', 'resolutions': [{'height': 81, 'url': 'https://preview.redd.it/cmmm9mzy566f1.jpeg?width=108&crop=smart&auto=webp&s=bb586f110a255b0ba2bfa09dd585983045449f5b', 'width': 108}, {'height': 162, 'url': 'https://preview.redd.it/cmmm9mzy566f1.jpeg?width=216&crop=smart&auto=webp&s=d3d7e325060c3b9686f8efd07d99e29a39d43b8a', 'width': 216}, {'height': 240, 'url': 'https://preview.redd.it/cmmm9mzy566f1.jpeg?width=320&crop=smart&auto=webp&s=7d628df72cf6b90874ff7e2c1ed52feaaeeee454', 'width': 320}, {'height': 480, 'url': 'https://preview.redd.it/cmmm9mzy566f1.jpeg?width=640&crop=smart&auto=webp&s=dbe495b4598c10b9779c611e27ce417d68244308', 'width': 640}, {'height': 720, 'url': 'https://preview.redd.it/cmmm9mzy566f1.jpeg?width=960&crop=smart&auto=webp&s=9df91a51c81b3e3a1d6985b77fe872bf8c52f282', 'width': 960}, {'height': 810, 'url': 'https://preview.redd.it/cmmm9mzy566f1.jpeg?width=1080&crop=smart&auto=webp&s=1f1ac6332bf83728ce4f29ba03399137fae089d3', 'width': 1080}], 'source': {'height': 3024, 'url': 'https://preview.redd.it/cmmm9mzy566f1.jpeg?auto=webp&s=d164bf9ab66dc4182df384a35e426fa6c9f3ff9c', 'width': 4032}, 'variants': {}}]} |
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Just got these in the mail! | 1 | [removed] | 2025-06-10T21:39:23 | heyitsapenguin | i.redd.it | 1970-01-01T00:00:00 | 0 | {} | 1l8b8fs | false | null | t3_1l8b8fs | /r/LocalLLaMA/comments/1l8b8fs/just_got_these_in_the_mail/ | false | false | 1 | {'enabled': True, 'images': [{'id': 'pQ2JT_g4rghF4ZDWp-4Jf_ncxA4DP7wtNmnhcs9Nco0', 'resolutions': [{'height': 81, 'url': 'https://preview.redd.it/3k9nm8iz566f1.jpeg?width=108&crop=smart&auto=webp&s=4fd27ee3bbfcf06cd3a5a357f8e40c6795421b1c', 'width': 108}, {'height': 162, 'url': 'https://preview.redd.it/3k9nm8iz566f1.jpeg?width=216&crop=smart&auto=webp&s=648159639b88f2d8cc8fdc17fa08237b9f3137bb', 'width': 216}, {'height': 240, 'url': 'https://preview.redd.it/3k9nm8iz566f1.jpeg?width=320&crop=smart&auto=webp&s=197d80dc8b086a53d68d109a60e69f69a35fa366', 'width': 320}, {'height': 480, 'url': 'https://preview.redd.it/3k9nm8iz566f1.jpeg?width=640&crop=smart&auto=webp&s=61d9f1881ac706c02d74cb16d3882d5e2e646c56', 'width': 640}, {'height': 720, 'url': 'https://preview.redd.it/3k9nm8iz566f1.jpeg?width=960&crop=smart&auto=webp&s=bcc451357a90f268232b62fd003193b3b3be31bc', 'width': 960}, {'height': 810, 'url': 'https://preview.redd.it/3k9nm8iz566f1.jpeg?width=1080&crop=smart&auto=webp&s=cb4107cdd8de353329ca737c7211b39fd0c9a9d3', 'width': 1080}], 'source': {'height': 3024, 'url': 'https://preview.redd.it/3k9nm8iz566f1.jpeg?auto=webp&s=aa360f6c341d946ebad9c6926882f05c763be1eb', 'width': 4032}, 'variants': {}}]} |
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Deepseek-r1-0528 is fire! | 312 | I just downloaded it last night and put it to work today. I'm no longer rushing to grab new models, I wait for the dust to settle, quants to be fixed and then grab it.
I'm not even doing anything agent with coding. Just zero shot prompting, 1613 lines of code generated. For this I had it generate an inventory management system. 14029 tokens. One shot and complete implementation.
prompt eval time = 79451.09 ms / 694 tokens ( 114.48 ms per token, 8.73 tokens per second)
eval time = 2721180.55 ms / 13335 tokens ( 204.06 ms per token, 4.90 tokens per second)
total time = 2800631.64 ms / 14029 tokens
Bananas!
https://preview.redd.it/cr58adlw666f1.png?width=754&format=png&auto=webp&s=8663bdc5a8815151d93f16a3e0749037c29655bf
https://preview.redd.it/9z7ihhsz666f1.png?width=1354&format=png&auto=webp&s=3b4359dd8ccb1a20a5ff840c738329f810e0fdba
https://preview.redd.it/eocred22766f1.png?width=1276&format=png&auto=webp&s=4400918ed42118b3298420bd70c4aa96b69f84a4
https://preview.redd.it/fdzkbg85766f1.png?width=1302&format=png&auto=webp&s=aa9fe81a44d3d10e934b3bb8e555024b6b4094a4
https://preview.redd.it/a77v9969766f1.png?width=1243&format=png&auto=webp&s=07b33955b549e1fb84a4a3a43a683460415509b9
| 2025-06-10T21:48:17 | https://www.reddit.com/r/LocalLLaMA/comments/1l8bgd2/deepseekr10528_is_fire/ | segmond | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1l8bgd2 | false | null | t3_1l8bgd2 | /r/LocalLLaMA/comments/1l8bgd2/deepseekr10528_is_fire/ | false | false | 312 | null |
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MiniSearch updated! Go deeper in your web research! | 47 | Hello r/LocalLLaMA!
Passing to invite you all to try the latest version of [MiniSearch](https://github.com/felladrin/MiniSearch), in which every follow-up question gathers more textual and graphical results to provide grounded answers. All links and images collected during a session will keep being listed, and the only limit will be your system memory.
You don't need to worry about context size, as the chat runs on a sliding window where the context is always kept under 4k tokens. Also, the web app is optimized to work on mobile browsers, so even on these devices you'll probably finish your research before running out of memory.
As mentioned in the [GitHub repository](https://github.com/felladrin/MiniSearch), you can run it on your machine via Docker, but for those willing to try without installing anything, there's a public instance available as a Hugging Face Space here:
[https://felladrin-minisearch.hf.space](https://felladrin-minisearch.hf.space)
Hope you enjoy it!
\---
P.S. MiniSearch is a pet project started two years ago, making use of small LLMs that can run directly in your browser and comment about the web search results, so that's what it defaults to. But for those who prefer using local inference engines (i.e. LM Studio, Ollama, vLLM) or cloud inference servers (i.e. OpenRouter, Glama, Infermatic), which can respond faster, they just need to select *"Remote server (API)"* in the *"AI Processing Location"* menu option, and configure their API Base URL, Access Key and Model. | 2025-06-10T22:15:19 | Felladrin | i.redd.it | 1970-01-01T00:00:00 | 0 | {} | 1l8c3nb | false | null | t3_1l8c3nb | /r/LocalLLaMA/comments/1l8c3nb/minisearch_updated_go_deeper_in_your_web_research/ | false | false | 47 | {'enabled': True, 'images': [{'id': 'XGx_gZV2FQx3Bz9VGVuS6HiWoQotPDFIzZEkUjt_6bw', 'resolutions': [{'height': 49, 'url': 'https://preview.redd.it/7zd0gvz2y56f1.png?width=108&crop=smart&auto=webp&s=0a7082cef712aff97a50de6546e277d008de0b3c', 'width': 108}, {'height': 99, 'url': 'https://preview.redd.it/7zd0gvz2y56f1.png?width=216&crop=smart&auto=webp&s=4ccc203c61182487a5d50efc66684bd8881b72bb', 'width': 216}, {'height': 146, 'url': 'https://preview.redd.it/7zd0gvz2y56f1.png?width=320&crop=smart&auto=webp&s=f083b32dd125f9b164cbaf3c7249031c67520812', 'width': 320}], 'source': {'height': 244, 'url': 'https://preview.redd.it/7zd0gvz2y56f1.png?auto=webp&s=28ff8d76de4d1f76df0dfe65651a9d3885311bb3', 'width': 532}, 'variants': {}}]} |
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AI for Family Photos: Seeking Expert Advice on Hardware and Software | 1 | [removed] | 2025-06-10T23:40:23 | https://www.reddit.com/r/LocalLLaMA/comments/1l8e110/ai_for_family_photos_seeking_expert_advice_on/ | GRC_Sparrow | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1l8e110 | false | null | t3_1l8e110 | /r/LocalLLaMA/comments/1l8e110/ai_for_family_photos_seeking_expert_advice_on/ | false | false | self | 1 | null |
Reverse engineer Claude Code to work with local models (and any OpenAI API) | 1 | 2025-06-10T23:41:00 | https://v.redd.it/kcqlqhear66f1 | sirvy3tr | /r/LocalLLaMA/comments/1l8e1jz/reverse_engineer_claude_code_to_work_with_local/ | 1970-01-01T00:00:00 | 0 | {} | 1l8e1jz | false | {'reddit_video': {'bitrate_kbps': 5000, 'dash_url': 'https://v.redd.it/kcqlqhear66f1/DASHPlaylist.mpd?a=1752320975%2CNDQ0MGIyOGM5MTdjOTJiOWYxMjA4MWJiZTUxNDljOTA0NGFiNzdhMWNjMDQzOGY0NTVjMWE4YjMxMmU1Mzk0OA%3D%3D&v=1&f=sd', 'duration': 64, 'fallback_url': 'https://v.redd.it/kcqlqhear66f1/DASH_1080.mp4?source=fallback', 'has_audio': False, 'height': 976, 'hls_url': 'https://v.redd.it/kcqlqhear66f1/HLSPlaylist.m3u8?a=1752320975%2CZWViNDA4ZTdlMGYzOTAyNjhhM2I5ZGZiY2NlZTBmMWExY2IwNDAyODliMmI0MGJmMmI2Y2IxYjIxNDVmZWZhYg%3D%3D&v=1&f=sd', 'is_gif': False, 'scrubber_media_url': 'https://v.redd.it/kcqlqhear66f1/DASH_96.mp4', 'transcoding_status': 'completed', 'width': 1920}} | t3_1l8e1jz | /r/LocalLLaMA/comments/1l8e1jz/reverse_engineer_claude_code_to_work_with_local/ | false | false | 1 | {'enabled': False, 'images': [{'id': 'bmc4ZDE2ZWFyNjZmMctWHYGqLFkRqe9fMU4vWS4S_srmoVFJV2NN56jF_ke4', 'resolutions': [{'height': 54, 'url': 'https://external-preview.redd.it/bmc4ZDE2ZWFyNjZmMctWHYGqLFkRqe9fMU4vWS4S_srmoVFJV2NN56jF_ke4.png?width=108&crop=smart&format=pjpg&auto=webp&s=f3223e4fd5eeabdc41e7c9ed8bc7ffbf37ba9be7', 'width': 108}, {'height': 109, 'url': 'https://external-preview.redd.it/bmc4ZDE2ZWFyNjZmMctWHYGqLFkRqe9fMU4vWS4S_srmoVFJV2NN56jF_ke4.png?width=216&crop=smart&format=pjpg&auto=webp&s=1d199afbc3eb21c11601d165439676f90fa51614', 'width': 216}, {'height': 162, 'url': 'https://external-preview.redd.it/bmc4ZDE2ZWFyNjZmMctWHYGqLFkRqe9fMU4vWS4S_srmoVFJV2NN56jF_ke4.png?width=320&crop=smart&format=pjpg&auto=webp&s=4daad977d6b602a9e14bf9698891d4552b3da5aa', 'width': 320}, {'height': 325, 'url': 'https://external-preview.redd.it/bmc4ZDE2ZWFyNjZmMctWHYGqLFkRqe9fMU4vWS4S_srmoVFJV2NN56jF_ke4.png?width=640&crop=smart&format=pjpg&auto=webp&s=8b84d3ce4d695846dfda68731d1453a696b68688', 'width': 640}, {'height': 487, 'url': 'https://external-preview.redd.it/bmc4ZDE2ZWFyNjZmMctWHYGqLFkRqe9fMU4vWS4S_srmoVFJV2NN56jF_ke4.png?width=960&crop=smart&format=pjpg&auto=webp&s=d007e635bef5df44748a93b940459ddaf70ca157', 'width': 960}, {'height': 548, 'url': 'https://external-preview.redd.it/bmc4ZDE2ZWFyNjZmMctWHYGqLFkRqe9fMU4vWS4S_srmoVFJV2NN56jF_ke4.png?width=1080&crop=smart&format=pjpg&auto=webp&s=6d1844f6793940bc351f5a0f569f3fa9d5955a29', 'width': 1080}], 'source': {'height': 1734, 'url': 'https://external-preview.redd.it/bmc4ZDE2ZWFyNjZmMctWHYGqLFkRqe9fMU4vWS4S_srmoVFJV2NN56jF_ke4.png?format=pjpg&auto=webp&s=7d75c361e1bc42b33cf84aeef823c68afccc9011', 'width': 3414}, 'variants': {}}]} |
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🔗 mistral.rs now has full built-in MCP Client support - Connect your local models to ANY external tool automatically! | 3 | Just shipped what I think is a game-changer for local LLM workflows: MCP (Model Context Protocol) client support in [mistral.rs](https://github.com/EricLBuehler/mistral.rs/) ([https://github.com/EricLBuehler/mistral.rs](https://github.com/EricLBuehler/mistral.rs))!
>**TL;DR:** [mistral.rs](https://github.com/EricLBuehler/mistral.rs) now has seamless built-in Model Context Protocol (MCP) support. No glue code - just config, run, and your model suddenly knows how to hit the file-system, REST endpoints, or WebSockets.
You can get [mistralrs via PyPi](https://github.com/EricLBuehler/mistral.rs/blob/master/mistralrs-pyo3/_README.md#installation-from-pypi), [Docker Containers](https://github.com/EricLBuehler/mistral.rs/pkgs/container/mistral.rs), or with [a local build](https://github.com/EricLBuehler/mistral.rs?tab=readme-ov-file#installation-and-build).
**What does this mean?**
Your models can now automatically connect to external tools and services - file systems, web search, databases, APIs, you name it.
No more manual tool calling setup, no more custom integration code.
Just configure once and your models gain superpowers.
We support all the transport interfaces:
* **Process**: Local tools (filesystem, databases, and more)
* **Streamable HTTP and SSE**: REST APIs, cloud services - Works with *any* HTTP MCP server
* **WebSocket**: Real-time streaming tools
**The best part?** ***It just works*****.** Tools are discovered automatically at startup. Multi-server support. Authentication handled. Timeouts managed.
I've been testing this extensively and it's incredibly smooth. The Python API feels natural, HTTP server integration is seamless, and the automatic tool discovery means no more maintaining tool registries.
**The magic ✨? It's just a few lines of Python.**
https://preview.redd.it/lr5bf5vjz56f1.png?width=1274&format=png&auto=webp&s=86901d7b7a9c0c82aca6983fc7bd932b5ec27d13
**Now your model can read/write files automatically when asked!**
**Use the HTTP server in just 2 steps:**
1) **Create mcp-config.json**
{
"servers": [
{
"name": "Filesystem Tools",
"source": {
"type": "Process",
"command": "npx",
"args": [
"@modelcontextprotocol/server-filesystem",
"."
]
}
}
],
"auto_register_tools": true
}
2) **Start server**
mistralrs-server --mcp-config mcp-config.json --port 1234 run -m Qwen/Qwen3-4B
**You can just use the normal OpenAI API - tools work automatically!**
curl -X POST http://localhost:1234/v1/chat/completions \
-H "Content-Type: application/json" \
-d '{
"model": "mistral.rs",
"messages": [
{
"role": "user",
"content": "List files and create hello.txt"
}
]
}'
What tools are you most excited to connect to your local models?
I'm excited to see what you create with this 🚀!
**Quick links:**
* [https://github.com/EricLBuehler/mistral.rs/blob/master/examples/MCP\_QUICK\_START.md](https://github.com/EricLBuehler/mistral.rs/blob/master/examples/MCP_QUICK_START.md)
* [https://github.com/EricLBuehler/mistral.rs/tree/master/docs/MCP](https://github.com/EricLBuehler/mistral.rs/tree/master/docs/MCP)
* [https://github.com/EricLBuehler/mistral.rs/blob/master/examples/python/mcp\_client.py](https://github.com/EricLBuehler/mistral.rs/blob/master/examples/python/mcp_client.py) | 2025-06-11T00:07:01 | https://www.reddit.com/r/LocalLLaMA/comments/1l8elh7/mistralrs_now_has_full_builtin_mcp_client_support/ | EricBuehler | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1l8elh7 | false | null | t3_1l8elh7 | /r/LocalLLaMA/comments/1l8elh7/mistralrs_now_has_full_builtin_mcp_client_support/ | false | false | 3 | {'enabled': False, 'images': [{'id': 'wYLtj87slRIDPIrbqMcHzlZxXZi3tCtil3ZBukqNvmk', 'resolutions': [{'height': 54, 'url': 'https://external-preview.redd.it/wYLtj87slRIDPIrbqMcHzlZxXZi3tCtil3ZBukqNvmk.png?width=108&crop=smart&auto=webp&s=a1589a4d4662f5346e04001a4de5de91901c0945', 'width': 108}, {'height': 108, 'url': 'https://external-preview.redd.it/wYLtj87slRIDPIrbqMcHzlZxXZi3tCtil3ZBukqNvmk.png?width=216&crop=smart&auto=webp&s=3d7ee54907b25a5ce4f9a7d6f0db1dfd6be0008a', 'width': 216}, {'height': 160, 'url': 'https://external-preview.redd.it/wYLtj87slRIDPIrbqMcHzlZxXZi3tCtil3ZBukqNvmk.png?width=320&crop=smart&auto=webp&s=6a7d3f2b240e7818d387d8fc2475bea1ce1416ce', 'width': 320}, {'height': 320, 'url': 'https://external-preview.redd.it/wYLtj87slRIDPIrbqMcHzlZxXZi3tCtil3ZBukqNvmk.png?width=640&crop=smart&auto=webp&s=1335b4728b7bc39b60880224863a2605b981daf8', 'width': 640}, {'height': 480, 'url': 'https://external-preview.redd.it/wYLtj87slRIDPIrbqMcHzlZxXZi3tCtil3ZBukqNvmk.png?width=960&crop=smart&auto=webp&s=3f336efa91ad5e2ec4e8811a4c44bbcb8e639452', 'width': 960}, {'height': 540, 'url': 'https://external-preview.redd.it/wYLtj87slRIDPIrbqMcHzlZxXZi3tCtil3ZBukqNvmk.png?width=1080&crop=smart&auto=webp&s=7217c6d5f28cb0932487b2ae8a454eeabfa82e98', 'width': 1080}], 'source': {'height': 600, 'url': 'https://external-preview.redd.it/wYLtj87slRIDPIrbqMcHzlZxXZi3tCtil3ZBukqNvmk.png?auto=webp&s=0da41884f7871959a6cc66ecc8417f036b8643bf', 'width': 1200}, 'variants': {}}]} |
|
Looking for a Clean DVD Copy of LM Studio (v0.2.x or Early 0.3.x) — Pre-Updater Poisoning | 1 | [removed] | 2025-06-11T00:35:01 | https://www.reddit.com/r/LocalLLaMA/comments/1l8f6e4/looking_for_a_clean_dvd_copy_of_lm_studio_v02x_or/ | Nervous-Exchange4597 | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1l8f6e4 | false | null | t3_1l8f6e4 | /r/LocalLLaMA/comments/1l8f6e4/looking_for_a_clean_dvd_copy_of_lm_studio_v02x_or/ | false | false | self | 1 | null |
Simple semantic search app to test Qwen3 embeddings | 1 | [removed] | 2025-06-11T00:36:53 | https://www.reddit.com/r/LocalLLaMA/comments/1l8f7sc/simple_semantic_search_app_to_test_qwen3/ | Extension_Leave9652 | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1l8f7sc | false | null | t3_1l8f7sc | /r/LocalLLaMA/comments/1l8f7sc/simple_semantic_search_app_to_test_qwen3/ | false | false | self | 1 | {'enabled': False, 'images': [{'id': 'w4h7U9wrVEfQT-8VnHCD0OixaYx1Qtnbf2_S-AaB9Wk', 'resolutions': [{'height': 54, 'url': 'https://external-preview.redd.it/w4h7U9wrVEfQT-8VnHCD0OixaYx1Qtnbf2_S-AaB9Wk.png?width=108&crop=smart&auto=webp&s=112e8d74729bc3f5c606ba4e913fc7212d6db3e6', 'width': 108}, {'height': 108, 'url': 'https://external-preview.redd.it/w4h7U9wrVEfQT-8VnHCD0OixaYx1Qtnbf2_S-AaB9Wk.png?width=216&crop=smart&auto=webp&s=2b674f02aa7b86338719a6eeb0a75ad06be77745', 'width': 216}, {'height': 160, 'url': 'https://external-preview.redd.it/w4h7U9wrVEfQT-8VnHCD0OixaYx1Qtnbf2_S-AaB9Wk.png?width=320&crop=smart&auto=webp&s=fc740911e48b75e24809960458497e817ab5de16', 'width': 320}, {'height': 320, 'url': 'https://external-preview.redd.it/w4h7U9wrVEfQT-8VnHCD0OixaYx1Qtnbf2_S-AaB9Wk.png?width=640&crop=smart&auto=webp&s=6ac1be4e80fc27a1c1cb4514505113bb93a9fc75', 'width': 640}, {'height': 480, 'url': 'https://external-preview.redd.it/w4h7U9wrVEfQT-8VnHCD0OixaYx1Qtnbf2_S-AaB9Wk.png?width=960&crop=smart&auto=webp&s=1dfec34cd6c87f539608b503c8d76a91b59155e0', 'width': 960}, {'height': 540, 'url': 'https://external-preview.redd.it/w4h7U9wrVEfQT-8VnHCD0OixaYx1Qtnbf2_S-AaB9Wk.png?width=1080&crop=smart&auto=webp&s=f3a8d0351eedcc560f81a65ecd83d76533198709', 'width': 1080}], 'source': {'height': 600, 'url': 'https://external-preview.redd.it/w4h7U9wrVEfQT-8VnHCD0OixaYx1Qtnbf2_S-AaB9Wk.png?auto=webp&s=d543d8c5d90a3a60b214d98e3a5ad623ddf7a89a', 'width': 1200}, 'variants': {}}]} |
📌 Title:
Looking for a Clean DVD Copy of LM Studio (v0.2.x or Early 0.3.x) — Pre-Updater Versions Only | 1 | [removed] | 2025-06-11T00:38:03 | https://www.reddit.com/r/LocalLLaMA/comments/1l8f8mt/title_looking_for_a_clean_dvd_copy_of_lm_studio/ | Nervous-Exchange4597 | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1l8f8mt | false | null | t3_1l8f8mt | /r/LocalLLaMA/comments/1l8f8mt/title_looking_for_a_clean_dvd_copy_of_lm_studio/ | false | false | self | 1 | null |
Has anyone tried Snowflake's Arctic Inference? Worth it for local setups ? | 1 | [removed] | 2025-06-11T00:38:59 | https://www.reddit.com/r/LocalLLaMA/comments/1l8f9bf/has_anyone_tried_snowflakes_arctic_inference/ | Raghuvansh_Tahlan | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1l8f9bf | false | null | t3_1l8f9bf | /r/LocalLLaMA/comments/1l8f9bf/has_anyone_tried_snowflakes_arctic_inference/ | false | false | self | 1 | null |
Looking for an Older LM Studio Copy — Early Versions Only | 1 | [removed] | 2025-06-11T00:39:32 | https://www.reddit.com/r/LocalLLaMA/comments/1l8f9ok/looking_for_an_older_lm_studio_copy_early/ | Nervous-Exchange4597 | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1l8f9ok | false | null | t3_1l8f9ok | /r/LocalLLaMA/comments/1l8f9ok/looking_for_an_older_lm_studio_copy_early/ | false | false | self | 1 | null |
Has anyone tried Snowflake's Arctic Inference? Worth it for local setups ? | 1 | [removed] | 2025-06-11T00:46:10 | https://www.reddit.com/r/LocalLLaMA/comments/1l8feo2/has_anyone_tried_snowflakes_arctic_inference/ | Raghuvansh_Tahlan | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1l8feo2 | false | null | t3_1l8feo2 | /r/LocalLLaMA/comments/1l8feo2/has_anyone_tried_snowflakes_arctic_inference/ | false | false | self | 1 | {'enabled': False, 'images': [{'id': 'OcPdNDE9h-KIzSuf6mtotvBCa3FL_-Rgj9tmVXzWlJs', 'resolutions': [{'height': 54, 'url': 'https://external-preview.redd.it/yu-cLG48ObnV5A_BenmhsjLpempvdEuAz3HDWiutmMM.jpg?width=108&crop=smart&auto=webp&s=53a1a9e28b97c47466885f2e82e2cf335f53fa25', 'width': 108}, {'height': 108, 'url': 'https://external-preview.redd.it/yu-cLG48ObnV5A_BenmhsjLpempvdEuAz3HDWiutmMM.jpg?width=216&crop=smart&auto=webp&s=3e6b83178ce5ed9d7dc4b3ce64f746c1bd873ae1', 'width': 216}, {'height': 160, 'url': 'https://external-preview.redd.it/yu-cLG48ObnV5A_BenmhsjLpempvdEuAz3HDWiutmMM.jpg?width=320&crop=smart&auto=webp&s=aecc225bcf05059af7f38879df0bf7a556d6fb0b', 'width': 320}, {'height': 320, 'url': 'https://external-preview.redd.it/yu-cLG48ObnV5A_BenmhsjLpempvdEuAz3HDWiutmMM.jpg?width=640&crop=smart&auto=webp&s=eff41fbb743455e3c9f2798e8764c27d017b62eb', 'width': 640}, {'height': 480, 'url': 'https://external-preview.redd.it/yu-cLG48ObnV5A_BenmhsjLpempvdEuAz3HDWiutmMM.jpg?width=960&crop=smart&auto=webp&s=e267918de9725f6cfc4537be5f951dcf2480479d', 'width': 960}, {'height': 540, 'url': 'https://external-preview.redd.it/yu-cLG48ObnV5A_BenmhsjLpempvdEuAz3HDWiutmMM.jpg?width=1080&crop=smart&auto=webp&s=a43e6e7f342d2a4b59cbf4a5b9f87e9258dbc119', 'width': 1080}], 'source': {'height': 600, 'url': 'https://external-preview.redd.it/yu-cLG48ObnV5A_BenmhsjLpempvdEuAz3HDWiutmMM.jpg?auto=webp&s=771f79291e1d2398afed2bfc895d79d5c8f70410', 'width': 1200}, 'variants': {}}]} |
Does generative engine optimization work? | 1 | [removed] | 2025-06-11T01:01:39 | https://www.reddit.com/r/LocalLLaMA/comments/1l8fpx6/does_generative_engine_optimization_work/ | compsedoc | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1l8fpx6 | false | null | t3_1l8fpx6 | /r/LocalLLaMA/comments/1l8fpx6/does_generative_engine_optimization_work/ | false | false | self | 1 | null |
'My Productivity Is At Zero': Meme Frenzy On Social Media As ChatGPT Goes Down Globally | 1 | https://www.google.com/amp/s/www.news18.com/amp/tech/my-productivity-is-at-zero-meme-frenzy-on-social-media-as-chatgpt-goes-down-globally-9378281.html
| 2025-06-11T01:03:54 | https://www.reddit.com/r/LocalLLaMA/comments/1l8frig/my_productivity_is_at_zero_meme_frenzy_on_social/ | siegevjorn | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1l8frig | false | null | t3_1l8frig | /r/LocalLLaMA/comments/1l8frig/my_productivity_is_at_zero_meme_frenzy_on_social/ | false | false | self | 1 | null |
venice.ai vs ollama on server | 0 | I have ollama installed on a vps. I'm all so looking at [venice.ai](http://venice.ai) . I just want to know witch one would you do | 2025-06-11T01:12:55 | https://www.reddit.com/r/LocalLLaMA/comments/1l8fxtl/veniceai_vs_ollama_on_server/ | wbiggs205 | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1l8fxtl | false | null | t3_1l8fxtl | /r/LocalLLaMA/comments/1l8fxtl/veniceai_vs_ollama_on_server/ | false | false | self | 0 | {'enabled': False, 'images': [{'id': 'rRDGOTZd1prv-7QHj5_Degzi3zpUKn55iTiFjQ3pvaY', 'resolutions': [{'height': 56, 'url': 'https://external-preview.redd.it/zx8qq2YSz3br54Y5q5Hyjtu-NCc5vbsE026WWlddR7o.jpg?width=108&crop=smart&auto=webp&s=ad7e4a70207be163e0c21e7ff4ec56eec0eb3920', 'width': 108}, {'height': 113, 'url': 'https://external-preview.redd.it/zx8qq2YSz3br54Y5q5Hyjtu-NCc5vbsE026WWlddR7o.jpg?width=216&crop=smart&auto=webp&s=d5c5b040f709968cc9823364ef49442ec50fff20', 'width': 216}, {'height': 168, 'url': 'https://external-preview.redd.it/zx8qq2YSz3br54Y5q5Hyjtu-NCc5vbsE026WWlddR7o.jpg?width=320&crop=smart&auto=webp&s=7d9294fdf6a62ec55d99057263a3bc0183a1bea3', 'width': 320}, {'height': 336, 'url': 'https://external-preview.redd.it/zx8qq2YSz3br54Y5q5Hyjtu-NCc5vbsE026WWlddR7o.jpg?width=640&crop=smart&auto=webp&s=55e24a5170b38102eb747abbf06eac7c6852fc54', 'width': 640}, {'height': 504, 'url': 'https://external-preview.redd.it/zx8qq2YSz3br54Y5q5Hyjtu-NCc5vbsE026WWlddR7o.jpg?width=960&crop=smart&auto=webp&s=69934e60f880b39ab03983e159133c5423164bb5', 'width': 960}, {'height': 567, 'url': 'https://external-preview.redd.it/zx8qq2YSz3br54Y5q5Hyjtu-NCc5vbsE026WWlddR7o.jpg?width=1080&crop=smart&auto=webp&s=30b7041cf53e3ea7ab8bd10f4a7bb501c1452674', 'width': 1080}], 'source': {'height': 1260, 'url': 'https://external-preview.redd.it/zx8qq2YSz3br54Y5q5Hyjtu-NCc5vbsE026WWlddR7o.jpg?auto=webp&s=00e1eedcc8449a316e1a251a4fe971854b8ad89f', 'width': 2400}, 'variants': {}}]} |
Meta to pay nearly $15 billion for Scale AI stake, The Information reports | 1 | June 10 (Reuters) - Meta Platforms [(META.O)](https://www.reuters.com/markets/companies/META.O)[, opens new tab](https://www.reuters.com/markets/companies/META.O) has agreed to take a 49% stake in artificial intelligence startup Scale AI for $14.8 billion, The Information reported on Tuesday, citing two people familiar with the matter.Founded in 2016, Scale AI provides vast amounts of labeled data or curated training data, which is crucial for developing sophisticated tools such as OpenAI's ChatGPT.
The Reuters Tariff Watch newsletter is your daily guide to the latest global trade and tariff news. Sign up [here.](https://www.reuters.com/newsletters/reuters-tariff-watch/?location=article-paragraph)
The deal, which has not been finalized yet, appears to be beneficial for Scale AI's investors including Accel, Index Ventures, Founders Fund and Greenoaks, as well as its current and former employees, the report said.Meta, Scale AI and the startup's investors did not immediately respond to Reuters' requests for [comment.As](http://comment.As) part of the deal, Scale AI CEO Alexandr Wang will take a top position inside Meta, leading a new ["superintelligence" lab](https://www.reuters.com/business/metas-zuckerberg-is-hiring-new-ai-team-bloomberg-news-reports-2025-06-10/), according to the report.Meta CEO Mark Zuckerberg has been actively recruiting top AI researchers to boost the company's AI efforts, the report said.The company is fighting the perception that it may have fallen behind in the AI race after its initial set of Llama 4 large language models [released in April](https://www.reuters.com/technology/meta-releases-new-ai-model-llama-4-2025-04-05/) fell short of performance expectations.Meta [delayed the release](https://www.reuters.com/business/meta-is-delaying-release-its-behemoth-ai-model-wsj-reports-2025-05-15/) of its flagship "Behemoth" AI model due to concerns about its capabilities, the Wall Street Journal reported last month.The company is also facing [antitrust concerns](https://www.reuters.com/sustainability/boards-policy-regulation/meta-asks-judge-rule-that-ftc-failed-prove-its-monopoly-case-2025-05-15/) related to its acquisitions of Instagram and WhatsApp.According to The Information report, the structure for the potential deal with Scale AI could be designed to avoid more regulatory scrutiny.Scale AI was valued at [$13.8 billion](https://www.reuters.com/technology/ai-startup-scale-ai-raises-1-billion-fresh-funding-2024-05-21/) in a funding round last spring. It generated about $870 million in revenue in 2024 and expects more than $2 billion this year, the report said.The company had more than $900 million of cash on its balance sheet at the end of last year, according to the report.June 10 (Reuters) - Meta Platforms (META.O)
, opens new tab has agreed to take a 49% stake in artificial intelligence startup Scale AI for $14.8 billion, The Information reported on Tuesday, citing two people familiar with the matter.
Founded in 2016, Scale AI provides vast amounts of labeled data or curated training data, which is crucial for developing sophisticated tools such as OpenAI's ChatGPT.
The Reuters Tariff Watch newsletter is your daily guide to the latest global trade and tariff news. Sign up here.
The deal, which has not been finalized yet, appears to be beneficial for Scale AI's investors including Accel, Index Ventures, Founders Fund and Greenoaks, as well as its current and former employees, the report said.
Meta, Scale AI and the startup's investors did not immediately respond to Reuters' requests for comment.
As part of the deal, Scale AI CEO Alexandr Wang will take a top position inside Meta, leading a new "superintelligence" lab, according to the report.
Meta CEO Mark Zuckerberg has been actively recruiting top AI researchers to boost the company's AI efforts, the report said.
The company is fighting the perception that it may have fallen behind in the AI race after its initial set of Llama 4 large language models released in April fell short of performance expectations.
Meta delayed the release of its flagship "Behemoth" AI model due to concerns about its capabilities, the Wall Street Journal reported last month.
The company is also facing antitrust concerns related to its acquisitions of Instagram and WhatsApp.
According to The Information report, the structure for the potential deal with Scale AI could be designed to avoid more regulatory scrutiny.
Scale AI was valued at $13.8 billion in a funding round last spring. It generated about $870 million in revenue in 2024 and expects more than $2 billion this year, the report said.
The company had more than $900 million of cash on its balance sheet at the end of last year, according to the report.June 10 (Reuters) - Meta Platforms (META.O), opens new tab has agreed to take a 49% stake in artificial intelligence startup Scale AI for $14.8 billion, The Information reported on Tuesday, citing two people familiar with the matter.
Founded in 2016, Scale AI provides vast amounts of labeled data or curated training data, which is crucial for developing sophisticated tools such as OpenAI's ChatGPT.
The Reuters Tariff Watch newsletter is your daily guide to the latest global trade and tariff news. Sign up here.
The deal, which has not been finalized yet, appears to be beneficial for Scale AI's investors including Accel, Index Ventures, Founders Fund and Greenoaks, as well as its current and former employees, the report said.
Meta, Scale AI and the startup's investors did not immediately respond to Reuters' requests for comment.
As part of the deal, Scale AI CEO Alexandr Wang will take a top position inside Meta, leading a new "superintelligence" lab, according to the report.
Meta CEO Mark Zuckerberg has been actively recruiting top AI researchers to boost the company's AI efforts, the report said.
The company is fighting the perception that it may have fallen behind in the AI race after its initial set of Llama 4 large language models released in April fell short of performance expectations.
Meta delayed the release of its flagship "Behemoth" AI model due to concerns about its capabilities, the Wall Street Journal reported last month.
The company is also facing antitrust concerns related to its acquisitions of Instagram and WhatsApp.
According to The Information report, the structure for the potential deal with Scale AI could be designed to avoid more regulatory scrutiny.
Scale AI was valued at $13.8 billion in a funding round last spring. It generated about $870 million in revenue in 2024 and expects more than $2 billion this year, the report said.
The company had more than $900 million of cash on its balance sheet at the end of last year, according to the report.Meta Platforms (the parent company of Facebook and Instagram) is finalizing a landmark deal to acquire a 49% stake in Scale AI, one of the leading data-labeling and AI infrastructure startups, for approximately $14.8–$15 billion[2](https://www.reuters.com/business/meta-pay-nearly-15-billion-scale-ai-stake-information-reports-2025-06-10/)[3](https://www.cnbc.com/2025/06/10/zuckerberg-makes-metas-biggest-bet-on-ai-14-billion-scale-ai-deal.html)[6](https://www.ft.com/content/5e556c2e-2ba4-415a-adb6-1bf6bed498eb)[7](https://cointelegraph.com/news/meta-acquires-49-percent-scale-ai-big-tech-ai-race)[8](https://www.theverge.com/news/684322/meta-scale-ai-15-billion-investment-zuckerberg)[9](https://finance.yahoo.com/news/meta-pay-nearly-15-billion-171801208.html). This is the largest external investment in Meta’s history and signals a major escalation in the competitive race among Big Tech firms to dominate artificial intelligence.
**Key Details of the Deal**
* **Stake and Valuation:** Meta will acquire a 49% stake in Scale AI, valuing the company at around $28–$30 billion[6](https://www.ft.com/content/5e556c2e-2ba4-415a-adb6-1bf6bed498eb)[8](https://www.theverge.com/news/684322/meta-scale-ai-15-billion-investment-zuckerberg).
* **Transaction Structure:** The deal is structured to avoid a full acquisition, likely to mitigate regulatory scrutiny, especially given Meta's ongoing antitrust issues related to previous acquisitions like Instagram and WhatsApp[2](https://www.reuters.com/business/meta-pay-nearly-15-billion-scale-ai-stake-information-reports-2025-06-10/)[3](https://www.cnbc.com/2025/06/10/zuckerberg-makes-metas-biggest-bet-on-ai-14-billion-scale-ai-deal.html)[4](https://www.newcomer.co/p/scale-ais-alexandr-wang-in-the-drivers)[9](https://finance.yahoo.com/news/meta-pay-nearly-15-billion-171801208.html).
* **Leadership Transition:** Alexandr Wang, Scale AI’s CEO and co-founder, will join Meta to lead a new “superintelligence” lab, bringing some top Scale AI talent with him[3](https://www.cnbc.com/2025/06/10/zuckerberg-makes-metas-biggest-bet-on-ai-14-billion-scale-ai-deal.html)[5](https://www.wsj.com/tech/ai/meta-in-talks-to-invest-14-billion-in-scale-ai-hire-ceo-alexandr-wang-5268564e)[8](https://www.theverge.com/news/684322/meta-scale-ai-15-billion-investment-zuckerberg). Wang will retain voting control over Scale AI, even as Meta becomes the largest outside shareholder[4](https://www.newcomer.co/p/scale-ais-alexandr-wang-in-the-drivers).
* **Investor Outcome:** The investment is reportedly structured as a dividend, allowing Scale AI’s investors and employees to realize significant returns while retaining some future upside[4](https://www.newcomer.co/p/scale-ais-alexandr-wang-in-the-drivers)[9](https://finance.yahoo.com/news/meta-pay-nearly-15-billion-171801208.html).
* **Revenue and Growth:** Scale AI reported $870 million in revenue for 2024 and expects to exceed $2 billion in 2025[2](https://www.reuters.com/business/meta-pay-nearly-15-billion-scale-ai-stake-information-reports-2025-06-10/)[8](https://www.theverge.com/news/684322/meta-scale-ai-15-billion-investment-zuckerberg)[9](https://finance.yahoo.com/news/meta-pay-nearly-15-billion-171801208.html).
# Strategic Rationale
**Why Meta Is Making This Move**
* **AI Catch-Up:** Meta has faced criticism for lagging behind rivals like OpenAI, Microsoft, Google, and Amazon in the AI arms race, particularly after the lukewarm reception of its Llama 4 models and the delayed launch of its “Behemoth” AI model[3](https://www.cnbc.com/2025/06/10/zuckerberg-makes-metas-biggest-bet-on-ai-14-billion-scale-ai-deal.html)[8](https://www.theverge.com/news/684322/meta-scale-ai-15-billion-investment-zuckerberg)[9](https://finance.yahoo.com/news/meta-pay-nearly-15-billion-171801208.html). The Scale AI deal is seen as an aggressive attempt to close this gap and accelerate progress toward artificial general intelligence (AGI)[7](https://cointelegraph.com/news/meta-acquires-49-percent-scale-ai-big-tech-ai-race)[8](https://www.theverge.com/news/684322/meta-scale-ai-15-billion-investment-zuckerberg).
* **Data and Infrastructure:** Scale AI is a critical provider of labeled data and curation services for training large AI models, serving clients such as OpenAI, Microsoft, Cohere, Google, and Meta itself[1](https://www.nytimes.com/2025/06/09/technology/meta-scale-ai-investment.html)[2](https://www.reuters.com/business/meta-pay-nearly-15-billion-scale-ai-stake-information-reports-2025-06-10/)[3](https://www.cnbc.com/2025/06/10/zuckerberg-makes-metas-biggest-bet-on-ai-14-billion-scale-ai-deal.html)[8](https://www.theverge.com/news/684322/meta-scale-ai-15-billion-investment-zuckerberg)[9](https://finance.yahoo.com/news/meta-pay-nearly-15-billion-171801208.html). By securing a large stake, Meta ensures privileged access to high-quality training data and infrastructure.
* **Talent Acquisition:** Bringing Alexandr Wang and key Scale AI personnel into Meta is expected to revitalize Meta’s AI leadership and technical capabilities[3](https://www.cnbc.com/2025/06/10/zuckerberg-makes-metas-biggest-bet-on-ai-14-billion-scale-ai-deal.html)[5](https://www.wsj.com/tech/ai/meta-in-talks-to-invest-14-billion-in-scale-ai-hire-ceo-alexandr-wang-5268564e)[8](https://www.theverge.com/news/684322/meta-scale-ai-15-billion-investment-zuckerberg).
* **Enterprise Expansion:** Meta plans to leverage its global sales force to expand Scale AI’s enterprise business, compensating for potential loss of business from rivals like Google and OpenAI, who may now see Scale AI as a competitor-aligned entity[4](https://www.newcomer.co/p/scale-ais-alexandr-wang-in-the-drivers).
# Industry and Competitive Context
* **Big Tech AI Bets:** This deal mirrors strategies by Microsoft (OpenAI), Amazon and Google (Anthropic), where major tech firms take large stakes in promising AI startups rather than outright acquisitions, partly to avoid antitrust complications and to secure long-term partnerships[3](https://www.cnbc.com/2025/06/10/zuckerberg-makes-metas-biggest-bet-on-ai-14-billion-scale-ai-deal.html)[8](https://www.theverge.com/news/684322/meta-scale-ai-15-billion-investment-zuckerberg).
* **Regulatory Sensitivities:** The structure of Meta’s investment—significant but non-controlling, with voting rights delegated to Wang—is designed to minimize regulatory risk and scrutiny[2](https://www.reuters.com/business/meta-pay-nearly-15-billion-scale-ai-stake-information-reports-2025-06-10/)[4](https://www.newcomer.co/p/scale-ais-alexandr-wang-in-the-drivers)[9](https://finance.yahoo.com/news/meta-pay-nearly-15-billion-171801208.html).
* **Sector Impact:** The move is likely to reshape the competitive landscape for AI infrastructure and data services, potentially reducing Scale AI’s business with Meta’s direct rivals while boosting its enterprise reach through Meta’s channels[4](https://www.newcomer.co/p/scale-ais-alexandr-wang-in-the-drivers).Meta Platforms (the parent company of Facebook and Instagram) is finalizing a landmark deal to acquire a 49% stake in Scale AI, one of the leading data-labeling and AI infrastructure startups, for approximately $14.8–$15 billion[2](https://www.reuters.com/business/meta-pay-nearly-15-billion-scale-ai-stake-information-reports-2025-06-10/)[3](https://www.cnbc.com/2025/06/10/zuckerberg-makes-metas-biggest-bet-on-ai-14-billion-scale-ai-deal.html)[6](https://www.ft.com/content/5e556c2e-2ba4-415a-adb6-1bf6bed498eb)[7](https://cointelegraph.com/news/meta-acquires-49-percent-scale-ai-big-tech-ai-race)[8](https://www.theverge.com/news/684322/meta-scale-ai-15-billion-investment-zuckerberg)[9](https://finance.yahoo.com/news/meta-pay-nearly-15-billion-171801208.html). This is the largest external investment in Meta’s history and signals a major escalation in the competitive race among Big Tech firms to dominate artificial intelligence.
**Key Details of the Deal**
* **Stake and Valuation:** Meta will acquire a 49% stake in Scale AI, valuing the company at around $28–$30 billion[6](https://www.ft.com/content/5e556c2e-2ba4-415a-adb6-1bf6bed498eb)[8](https://www.theverge.com/news/684322/meta-scale-ai-15-billion-investment-zuckerberg).
* **Transaction Structure:** The deal is structured to avoid a full acquisition, likely to mitigate regulatory scrutiny, especially given Meta's ongoing antitrust issues related to previous acquisitions like Instagram and WhatsApp[2](https://www.reuters.com/business/meta-pay-nearly-15-billion-scale-ai-stake-information-reports-2025-06-10/)[3](https://www.cnbc.com/2025/06/10/zuckerberg-makes-metas-biggest-bet-on-ai-14-billion-scale-ai-deal.html)[4](https://www.newcomer.co/p/scale-ais-alexandr-wang-in-the-drivers)[9](https://finance.yahoo.com/news/meta-pay-nearly-15-billion-171801208.html).
* **Leadership Transition:** Alexandr Wang, Scale AI’s CEO and co-founder, will join Meta to lead a new “superintelligence” lab, bringing some top Scale AI talent with him[3](https://www.cnbc.com/2025/06/10/zuckerberg-makes-metas-biggest-bet-on-ai-14-billion-scale-ai-deal.html)[5](https://www.wsj.com/tech/ai/meta-in-talks-to-invest-14-billion-in-scale-ai-hire-ceo-alexandr-wang-5268564e)[8](https://www.theverge.com/news/684322/meta-scale-ai-15-billion-investment-zuckerberg). Wang will retain voting control over Scale AI, even as Meta becomes the largest outside shareholder[4](https://www.newcomer.co/p/scale-ais-alexandr-wang-in-the-drivers).
* **Investor Outcome:** The investment is reportedly structured as a dividend, allowing Scale AI’s investors and employees to realize significant returns while retaining some future upside[4](https://www.newcomer.co/p/scale-ais-alexandr-wang-in-the-drivers)[9](https://finance.yahoo.com/news/meta-pay-nearly-15-billion-171801208.html).
* **Revenue and Growth:** Scale AI reported $870 million in revenue for 2024 and expects to exceed $2 billion in 2025[2](https://www.reuters.com/business/meta-pay-nearly-15-billion-scale-ai-stake-information-reports-2025-06-10/)[8](https://www.theverge.com/news/684322/meta-scale-ai-15-billion-investment-zuckerberg)[9](https://finance.yahoo.com/news/meta-pay-nearly-15-billion-171801208.html).
# Strategic Rationale
**Why Meta Is Making This Move**
* **AI Catch-Up:** Meta has faced criticism for lagging behind rivals like OpenAI, Microsoft, Google, and Amazon in the AI arms race, particularly after the lukewarm reception of its Llama 4 models and the delayed launch of its “Behemoth” AI model[3](https://www.cnbc.com/2025/06/10/zuckerberg-makes-metas-biggest-bet-on-ai-14-billion-scale-ai-deal.html)[8](https://www.theverge.com/news/684322/meta-scale-ai-15-billion-investment-zuckerberg)[9](https://finance.yahoo.com/news/meta-pay-nearly-15-billion-171801208.html). The Scale AI deal is seen as an aggressive attempt to close this gap and accelerate progress toward artificial general intelligence (AGI)[7](https://cointelegraph.com/news/meta-acquires-49-percent-scale-ai-big-tech-ai-race)[8](https://www.theverge.com/news/684322/meta-scale-ai-15-billion-investment-zuckerberg).
* **Data and Infrastructure:** Scale AI is a critical provider of labeled data and curation services for training large AI models, serving clients such as OpenAI, Microsoft, Cohere, Google, and Meta itself[1](https://www.nytimes.com/2025/06/09/technology/meta-scale-ai-investment.html)[2](https://www.reuters.com/business/meta-pay-nearly-15-billion-scale-ai-stake-information-reports-2025-06-10/)[3](https://www.cnbc.com/2025/06/10/zuckerberg-makes-metas-biggest-bet-on-ai-14-billion-scale-ai-deal.html)[8](https://www.theverge.com/news/684322/meta-scale-ai-15-billion-investment-zuckerberg)[9](https://finance.yahoo.com/news/meta-pay-nearly-15-billion-171801208.html). By securing a large stake, Meta ensures privileged access to high-quality training data and infrastructure.
* **Talent Acquisition:** Bringing Alexandr Wang and key Scale AI personnel into Meta is expected to revitalize Meta’s AI leadership and technical capabilities[3](https://www.cnbc.com/2025/06/10/zuckerberg-makes-metas-biggest-bet-on-ai-14-billion-scale-ai-deal.html)[5](https://www.wsj.com/tech/ai/meta-in-talks-to-invest-14-billion-in-scale-ai-hire-ceo-alexandr-wang-5268564e)[8](https://www.theverge.com/news/684322/meta-scale-ai-15-billion-investment-zuckerberg).
* **Enterprise Expansion:** Meta plans to leverage its global sales force to expand Scale AI’s enterprise business, compensating for potential loss of business from rivals like Google and OpenAI, who may now see Scale AI as a competitor-aligned entity[4](https://www.newcomer.co/p/scale-ais-alexandr-wang-in-the-drivers).
# Industry and Competitive Context
* **Big Tech AI Bets:** This deal mirrors strategies by Microsoft (OpenAI), Amazon and Google (Anthropic), where major tech firms take large stakes in promising AI startups rather than outright acquisitions, partly to avoid antitrust complications and to secure long-term partnerships[3](https://www.cnbc.com/2025/06/10/zuckerberg-makes-metas-biggest-bet-on-ai-14-billion-scale-ai-deal.html)[8](https://www.theverge.com/news/684322/meta-scale-ai-15-billion-investment-zuckerberg).
* **Regulatory Sensitivities:** The structure of Meta’s investment—significant but non-controlling, with voting rights delegated to Wang—is designed to minimize regulatory risk and scrutiny[2](https://www.reuters.com/business/meta-pay-nearly-15-billion-scale-ai-stake-information-reports-2025-06-10/)[4](https://www.newcomer.co/p/scale-ais-alexandr-wang-in-the-drivers)[9](https://finance.yahoo.com/news/meta-pay-nearly-15-billion-171801208.html).
* **Sector Impact:** The move is likely to reshape the competitive landscape for AI infrastructure and data services, potentially reducing Scale AI’s business with Meta’s direct rivals while boosting its enterprise reach through Meta’s channels[4](https://www.newcomer.co/p/scale-ais-alexandr-wang-in-the-drivers).Meta Platforms (the parent company of Facebook and Instagram) is finalizing a landmark deal to acquire a 49% stake in Scale AI, one of the leading data-labeling and AI infrastructure startups, for approximately $14.8–$15 billion[2](https://www.reuters.com/business/meta-pay-nearly-15-billion-scale-ai-stake-information-reports-2025-06-10/)[3](https://www.cnbc.com/2025/06/10/zuckerberg-makes-metas-biggest-bet-on-ai-14-billion-scale-ai-deal.html)[6](https://www.ft.com/content/5e556c2e-2ba4-415a-adb6-1bf6bed498eb)[7](https://cointelegraph.com/news/meta-acquires-49-percent-scale-ai-big-tech-ai-race)[8](https://www.theverge.com/news/684322/meta-scale-ai-15-billion-investment-zuckerberg)[9](https://finance.yahoo.com/news/meta-pay-nearly-15-billion-171801208.html). This is the largest external investment in Meta’s history and signals a major escalation in the competitive race among Big Tech firms to dominate artificial intelligence.
**Key Details of the Deal**
* **Stake and Valuation:** Meta will acquire a 49% stake in Scale AI, valuing the company at around $28–$30 billion[6](https://www.ft.com/content/5e556c2e-2ba4-415a-adb6-1bf6bed498eb)[8](https://www.theverge.com/news/684322/meta-scale-ai-15-billion-investment-zuckerberg).
* **Transaction Structure:** The deal is structured to avoid a full acquisition, likely to mitigate regulatory scrutiny, especially given Meta's ongoing antitrust issues related to previous acquisitions like Instagram and WhatsApp[2](https://www.reuters.com/business/meta-pay-nearly-15-billion-scale-ai-stake-information-reports-2025-06-10/)[3](https://www.cnbc.com/2025/06/10/zuckerberg-makes-metas-biggest-bet-on-ai-14-billion-scale-ai-deal.html)[4](https://www.newcomer.co/p/scale-ais-alexandr-wang-in-the-drivers)[9](https://finance.yahoo.com/news/meta-pay-nearly-15-billion-171801208.html).
* **Leadership Transition:** Alexandr Wang, Scale AI’s CEO and co-founder, will join Meta to lead a new “superintelligence” lab, bringing some top Scale AI talent with him[3](https://www.cnbc.com/2025/06/10/zuckerberg-makes-metas-biggest-bet-on-ai-14-billion-scale-ai-deal.html)[5](https://www.wsj.com/tech/ai/meta-in-talks-to-invest-14-billion-in-scale-ai-hire-ceo-alexandr-wang-5268564e)[8](https://www.theverge.com/news/684322/meta-scale-ai-15-billion-investment-zuckerberg). Wang will retain voting control over Scale AI, even as Meta becomes the largest outside shareholder[4](https://www.newcomer.co/p/scale-ais-alexandr-wang-in-the-drivers).
* **Investor Outcome:** The investment is reportedly structured as a dividend, allowing Scale AI’s investors and employees to realize significant returns while retaining some future upside[4](https://www.newcomer.co/p/scale-ais-alexandr-wang-in-the-drivers)[9](https://finance.yahoo.com/news/meta-pay-nearly-15-billion-171801208.html).
* **Revenue and Growth:** Scale AI reported $870 million in revenue for 2024 and expects to exceed $2 billion in 2025[2](https://www.reuters.com/business/meta-pay-nearly-15-billion-scale-ai-stake-information-reports-2025-06-10/)[8](https://www.theverge.com/news/684322/meta-scale-ai-15-billion-investment-zuckerberg)[9](https://finance.yahoo.com/news/meta-pay-nearly-15-billion-171801208.html).
# Strategic Rationale
**Why Meta Is Making This Move**
* **AI Catch-Up:** Meta has faced criticism for lagging behind rivals like OpenAI, Microsoft, Google, and Amazon in the AI arms race, particularly after the lukewarm reception of its Llama 4 models and the delayed launch of its “Behemoth” AI model[3](https://www.cnbc.com/2025/06/10/zuckerberg-makes-metas-biggest-bet-on-ai-14-billion-scale-ai-deal.html)[8](https://www.theverge.com/news/684322/meta-scale-ai-15-billion-investment-zuckerberg)[9](https://finance.yahoo.com/news/meta-pay-nearly-15-billion-171801208.html). The Scale AI deal is seen as an aggressive attempt to close this gap and accelerate progress toward artificial general intelligence (AGI)[7](https://cointelegraph.com/news/meta-acquires-49-percent-scale-ai-big-tech-ai-race)[8](https://www.theverge.com/news/684322/meta-scale-ai-15-billion-investment-zuckerberg).
* **Data and Infrastructure:** Scale AI is a critical provider of labeled data and curation services for training large AI models, serving clients such as OpenAI, Microsoft, Cohere, Google, and Meta itself[1](https://www.nytimes.com/2025/06/09/technology/meta-scale-ai-investment.html)[2](https://www.reuters.com/business/meta-pay-nearly-15-billion-scale-ai-stake-information-reports-2025-06-10/)[3](https://www.cnbc.com/2025/06/10/zuckerberg-makes-metas-biggest-bet-on-ai-14-billion-scale-ai-deal.html)[8](https://www.theverge.com/news/684322/meta-scale-ai-15-billion-investment-zuckerberg)[9](https://finance.yahoo.com/news/meta-pay-nearly-15-billion-171801208.html). By securing a large stake, Meta ensures privileged access to high-quality training data and infrastructure.
* **Talent Acquisition:** Bringing Alexandr Wang and key Scale AI personnel into Meta is expected to revitalize Meta’s AI leadership and technical capabilities[3](https://www.cnbc.com/2025/06/10/zuckerberg-makes-metas-biggest-bet-on-ai-14-billion-scale-ai-deal.html)[5](https://www.wsj.com/tech/ai/meta-in-talks-to-invest-14-billion-in-scale-ai-hire-ceo-alexandr-wang-5268564e)[8](https://www.theverge.com/news/684322/meta-scale-ai-15-billion-investment-zuckerberg).
* **Enterprise Expansion:** Meta plans to leverage its global sales force to expand Scale AI’s enterprise business, compensating for potential loss of business from rivals like Google and OpenAI, who may now see Scale AI as a competitor-aligned entity[4](https://www.newcomer.co/p/scale-ais-alexandr-wang-in-the-drivers).
# Industry and Competitive Context
* **Big Tech AI Bets:** This deal mirrors strategies by Microsoft (OpenAI), Amazon and Google (Anthropic), where major tech firms take large stakes in promising AI startups rather than outright acquisitions, partly to avoid antitrust complications and to secure long-term partnerships[3](https://www.cnbc.com/2025/06/10/zuckerberg-makes-metas-biggest-bet-on-ai-14-billion-scale-ai-deal.html)[8](https://www.theverge.com/news/684322/meta-scale-ai-15-billion-investment-zuckerberg).
* **Regulatory Sensitivities:** The structure of Meta’s investment—significant but non-controlling, with voting rights delegated to Wang—is designed to minimize regulatory risk and scrutiny[2](https://www.reuters.com/business/meta-pay-nearly-15-billion-scale-ai-stake-information-reports-2025-06-10/)[4](https://www.newcomer.co/p/scale-ais-alexandr-wang-in-the-drivers)[9](https://finance.yahoo.com/news/meta-pay-nearly-15-billion-171801208.html).
* **Sector Impact:** The move is likely to reshape the competitive landscape for AI infrastructure and data services, potentially reducing Scale AI’s business with Meta’s direct rivals while boosting its enterprise reach through Meta’s channels[4](https://www.newcomer.co/p/scale-ais-alexandr-wang-in-the-drivers).
June 10 (Reuters) - Meta Platforms [(META.O)](https://www.reuters.com/markets/companies/META.O)[, opens new tab](https://www.reuters.com/markets/companies/META.O) has agreed to take a 49% stake in artificial intelligence startup Scale AI for $14.8 billion, The Information reported on Tuesday, citing two people familiar with the matter.Founded in 2016, Scale AI provides vast amounts of labeled data or curated training data, which is crucial for developing sophisticated tools such as OpenAI's ChatGPT.
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The deal, which has not been finalized yet, appears to be beneficial for Scale AI's investors including Accel, Index Ventures, Founders Fund and Greenoaks, as well as its current and former employees, the report said.Meta, Scale AI and the startup's investors did not immediately respond to Reuters' requests for [comment.As](http://comment.As) part of the deal, Scale AI CEO Alexandr Wang will take a top position inside Meta, leading a new ["superintelligence" lab](https://www.reuters.com/business/metas-zuckerberg-is-hiring-new-ai-team-bloomberg-news-reports-2025-06-10/), according to the report.Meta CEO Mark Zuckerberg has been actively recruiting top AI researchers to boost the company's AI efforts, the report said.The company is fighting the perception that it may have fallen behind in the AI race after its initial set of Llama 4 large language models [released in April](https://www.reuters.com/technology/meta-releases-new-ai-model-llama-4-2025-04-05/) fell short of performance expectations.Meta [delayed the release](https://www.reuters.com/business/meta-is-delaying-release-its-behemoth-ai-model-wsj-reports-2025-05-15/) of its flagship "Behemoth" AI model due to concerns about its capabilities, the Wall Street Journal reported last month.The company is also facing [antitrust concerns](https://www.reuters.com/sustainability/boards-policy-regulation/meta-asks-judge-rule-that-ftc-failed-prove-its-monopoly-case-2025-05-15/) related to its acquisitions of Instagram and WhatsApp.According to The Information report, the structure for the potential deal with Scale AI could be designed to avoid more regulatory scrutiny.Scale AI was valued at [$13.8 billion](https://www.reuters.com/technology/ai-startup-scale-ai-raises-1-billion-fresh-funding-2024-05-21/) in a funding round last spring. It generated about $870 million in revenue in 2024 and expects more than $2 billion this year, the report said.The company had more than $900 million of cash on its balance sheet at the end of last year, according to the report. | 2025-06-11T01:30:21 | https://www.reuters.com/business/meta-pay-nearly-15-billion-scale-ai-stake-information-reports-2025-06-10/ | Vatnik_Annihilator | reuters.com | 1970-01-01T00:00:00 | 0 | {} | 1l8ga2w | false | null | t3_1l8ga2w | /r/LocalLLaMA/comments/1l8ga2w/meta_to_pay_nearly_15_billion_for_scale_ai_stake/ | false | false | 1 | {'enabled': False, 'images': [{'id': 'U-NXckJd-ahQHc3V5x4ph9oZyPpjG9eIkfbSC_aHu8I', 'resolutions': [{'height': 56, 'url': 'https://external-preview.redd.it/RWnBj-m9OL2YChixPfK99gwnogICJmHOW0j8MrU__kM.jpg?width=108&crop=smart&auto=webp&s=2066895ce3eb7802d4c587c8310ad283ca79c924', 'width': 108}, {'height': 113, 'url': 'https://external-preview.redd.it/RWnBj-m9OL2YChixPfK99gwnogICJmHOW0j8MrU__kM.jpg?width=216&crop=smart&auto=webp&s=43f22248af05dee588326ca9f8ec09ee4e733920', 'width': 216}, {'height': 167, 'url': 'https://external-preview.redd.it/RWnBj-m9OL2YChixPfK99gwnogICJmHOW0j8MrU__kM.jpg?width=320&crop=smart&auto=webp&s=712b6bc32b56c94bb5d665120b417a34b71d2761', 'width': 320}, {'height': 335, 'url': 'https://external-preview.redd.it/RWnBj-m9OL2YChixPfK99gwnogICJmHOW0j8MrU__kM.jpg?width=640&crop=smart&auto=webp&s=836acaf541c15ede6377db1512c4ff2ceac17832', 'width': 640}, {'height': 502, 'url': 'https://external-preview.redd.it/RWnBj-m9OL2YChixPfK99gwnogICJmHOW0j8MrU__kM.jpg?width=960&crop=smart&auto=webp&s=7f8cbb44bfa9fabe3052b6cc32e5bac94ef5830f', 'width': 960}, {'height': 565, 'url': 'https://external-preview.redd.it/RWnBj-m9OL2YChixPfK99gwnogICJmHOW0j8MrU__kM.jpg?width=1080&crop=smart&auto=webp&s=fdcaff4d1690da57e03fe1a07d883f133433b1f9', 'width': 1080}], 'source': {'height': 1005, 'url': 'https://external-preview.redd.it/RWnBj-m9OL2YChixPfK99gwnogICJmHOW0j8MrU__kM.jpg?auto=webp&s=66674b5f2d6da0d8c880882badde2dbebd064191', 'width': 1920}, 'variants': {}}]} |
|
You can chat with iOS’ local LLM on iOS 26 | 1 | [removed] | 2025-06-11T01:35:27 | Weak_Tie1467 | i.redd.it | 1970-01-01T00:00:00 | 0 | {} | 1l8gdqt | false | null | t3_1l8gdqt | /r/LocalLLaMA/comments/1l8gdqt/you_can_chat_with_ios_local_llm_on_ios_26/ | false | false | 1 | {'enabled': True, 'images': [{'id': '9VcLUY1pPKjavQr_rA-GBE5Ub4QcJY5cUizyN2ISTvs', 'resolutions': [{'height': 92, 'url': 'https://preview.redd.it/4qitb3n3c76f1.jpeg?width=108&crop=smart&auto=webp&s=394f81be06440ec61a5b30dcde7abfb537a75df1', 'width': 108}, {'height': 184, 'url': 'https://preview.redd.it/4qitb3n3c76f1.jpeg?width=216&crop=smart&auto=webp&s=6721520bf9e5421c76de2fba5c76d5ad3cc9989c', 'width': 216}, {'height': 273, 'url': 'https://preview.redd.it/4qitb3n3c76f1.jpeg?width=320&crop=smart&auto=webp&s=d430a74b12e4db9a860c149d9cf38e48d67fd8be', 'width': 320}, {'height': 546, 'url': 'https://preview.redd.it/4qitb3n3c76f1.jpeg?width=640&crop=smart&auto=webp&s=b34d6b76a222c056bdc98c45e95b6697cb069539', 'width': 640}, {'height': 820, 'url': 'https://preview.redd.it/4qitb3n3c76f1.jpeg?width=960&crop=smart&auto=webp&s=24ee2028bee3e0c23cfdcc748553bc88e135fae5', 'width': 960}, {'height': 922, 'url': 'https://preview.redd.it/4qitb3n3c76f1.jpeg?width=1080&crop=smart&auto=webp&s=7f8de1f1b698f968b8aa761c8fe21ba39fb3f8d4', 'width': 1080}], 'source': {'height': 1128, 'url': 'https://preview.redd.it/4qitb3n3c76f1.jpeg?auto=webp&s=26cfb8dcfb6b0b8cd83c4b0b5a796f18169a90a4', 'width': 1320}, 'variants': {}}]} |
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Meta to pay nearly $15 billion for Scale AI stake, The Information reports | 96 | Meta’s investment in Scale AI—reportedly valued between $14 billion and $15 billion for a 49% stake—signals a pivotal shift in the tech giant’s artificial intelligence strategy and has broad implications for the AI industry, Meta’s competitive position, and the broader landscape of AI infrastructure[3](https://www.washingtonpost.com/technology/2025/06/10/ai-meta-scale-google-openai/)[10](https://www.reuters.com/business/meta-pay-nearly-15-billion-scale-ai-stake-information-reports-2025-06-10/)[13](https://www.theverge.com/news/684322/meta-scale-ai-15-billion-investment-zuckerberg).
# Strategic Impact on Meta
* **Accelerated AI Development:** The investment provides Meta with direct access to Scale AI’s advanced data labeling and curation services, which are critical for training large language models (LLMs) and other AI systems. This will help Meta overcome recent challenges, such as the underwhelming launch of its Llama AI models and the postponed release of its next-gen “Behemoth” system[7](https://www.cnbc.com/2025/06/10/zuckerberg-makes-metas-biggest-bet-on-ai-14-billion-scale-ai-deal.html)[9](https://www.ainvest.com/news/meta-14-8b-scale-ai-stake-land-grab-agi-supremacy-2506/)[13](https://www.theverge.com/news/684322/meta-scale-ai-15-billion-investment-zuckerberg).
* **Talent Acquisition:** Scale AI’s CEO, Alexandr Wang, is set to lead a new “superintelligence” lab at Meta, bringing with him a team of experts focused on artificial general intelligence (AGI). This move addresses Meta’s struggles with high turnover and project delays in its AI division[8](https://www.ainvest.com/news/meta-invests-14-billion-scale-ai-hires-founder-alexandr-wang-lead-ai-lab-2506/)[11](https://www.wsj.com/tech/ai/meta-in-talks-to-invest-14-billion-in-scale-ai-hire-ceo-alexandr-wang-5268564e)[13](https://www.theverge.com/news/684322/meta-scale-ai-15-billion-investment-zuckerberg).
* **Enhanced Data Infrastructure:** By securing a steady supply of high-quality, specialized data, Meta aims to future-proof its AI pipeline, supporting not only its consumer-facing products but also its enterprise and defense initiatives, such as the “Defense Llama” project[6](https://www.ainvest.com/news/meta-10-billion-bet-scale-ai-strategic-play-dominance-ai-data-infrastructure-2506/)[9](https://www.ainvest.com/news/meta-14-8b-scale-ai-stake-land-grab-agi-supremacy-2506/)[13](https://www.theverge.com/news/684322/meta-scale-ai-15-billion-investment-zuckerberg).
# Industry and Competitive Dynamics
* **Race for AI Supremacy:** Meta’s investment is part of a broader trend among Big Tech companies to secure foundational AI infrastructure. Microsoft, Google, and Amazon have made similar bets by investing billions in OpenAI, Anthropic, and other AI startups[4](https://fortune.com/2025/06/08/meta-scale-ai-statup-investment-10-billion-alexandr-wang-machine-learning/)[13](https://www.theverge.com/news/684322/meta-scale-ai-15-billion-investment-zuckerberg).
* **Market Valuation and Growth:** Scale AI’s valuation is expected to double to nearly $28 billion post-investment, reflecting the premium placed on AI data infrastructure in today’s market. The company’s revenue is projected to more than double from $870 million in 2024 to over $2 billion in 2025[9](https://www.ainvest.com/news/meta-14-8b-scale-ai-stake-land-grab-agi-supremacy-2506/)[13](https://www.theverge.com/news/684322/meta-scale-ai-15-billion-investment-zuckerberg).
* **Regulatory and Antitrust Considerations:** By taking a minority stake rather than a full acquisition, Meta avoids some of the regulatory scrutiny that might accompany a complete takeover, while still securing significant influence and access to Scale AI’s resources[7](https://www.cnbc.com/2025/06/10/zuckerberg-makes-metas-biggest-bet-on-ai-14-billion-scale-ai-deal.html)[9](https://www.ainvest.com/news/meta-14-8b-scale-ai-stake-land-grab-agi-supremacy-2506/).
# Broader Implications
* **AI Infrastructure as a Strategic Asset:** The deal underscores the growing importance of data labeling and curation as a critical utility in the AI economy. Companies that control these resources are better positioned to compete in both commercial and governmental AI markets[6](https://www.ainvest.com/news/meta-10-billion-bet-scale-ai-strategic-play-dominance-ai-data-infrastructure-2506/)[9](https://www.ainvest.com/news/meta-14-8b-scale-ai-stake-land-grab-agi-supremacy-2506/).
* **Investment and Innovation:** For investors, the partnership signals a shift toward betting on AI infrastructure over individual applications. It highlights the potential for long-term growth in companies that provide the foundational tools for AI development[6](https://www.ainvest.com/news/meta-10-billion-bet-scale-ai-strategic-play-dominance-ai-data-infrastructure-2506/)[9](https://www.ainvest.com/news/meta-14-8b-scale-ai-stake-land-grab-agi-supremacy-2506/).
* **Challenges and Risks:** Despite the strategic benefits, Meta and Scale AI face potential risks, including concerns over labor practices, data confidentiality (given Scale AI’s work with competitors), and the ongoing need to navigate regulatory environments[6](https://www.ainvest.com/news/meta-10-billion-bet-scale-ai-strategic-play-dominance-ai-data-infrastructure-2506/). | 2025-06-11T01:38:51 | https://www.reuters.com/business/meta-pay-nearly-15-billion-scale-ai-stake-information-reports-2025-06-10/ | Vatnik_Annihilator | reuters.com | 1970-01-01T00:00:00 | 0 | {} | 1l8gg51 | false | null | t3_1l8gg51 | /r/LocalLLaMA/comments/1l8gg51/meta_to_pay_nearly_15_billion_for_scale_ai_stake/ | false | false | 96 | {'enabled': False, 'images': [{'id': 'U-NXckJd-ahQHc3V5x4ph9oZyPpjG9eIkfbSC_aHu8I', 'resolutions': [{'height': 56, 'url': 'https://external-preview.redd.it/RWnBj-m9OL2YChixPfK99gwnogICJmHOW0j8MrU__kM.jpg?width=108&crop=smart&auto=webp&s=2066895ce3eb7802d4c587c8310ad283ca79c924', 'width': 108}, {'height': 113, 'url': 'https://external-preview.redd.it/RWnBj-m9OL2YChixPfK99gwnogICJmHOW0j8MrU__kM.jpg?width=216&crop=smart&auto=webp&s=43f22248af05dee588326ca9f8ec09ee4e733920', 'width': 216}, {'height': 167, 'url': 'https://external-preview.redd.it/RWnBj-m9OL2YChixPfK99gwnogICJmHOW0j8MrU__kM.jpg?width=320&crop=smart&auto=webp&s=712b6bc32b56c94bb5d665120b417a34b71d2761', 'width': 320}, {'height': 335, 'url': 'https://external-preview.redd.it/RWnBj-m9OL2YChixPfK99gwnogICJmHOW0j8MrU__kM.jpg?width=640&crop=smart&auto=webp&s=836acaf541c15ede6377db1512c4ff2ceac17832', 'width': 640}, {'height': 502, 'url': 'https://external-preview.redd.it/RWnBj-m9OL2YChixPfK99gwnogICJmHOW0j8MrU__kM.jpg?width=960&crop=smart&auto=webp&s=7f8cbb44bfa9fabe3052b6cc32e5bac94ef5830f', 'width': 960}, {'height': 565, 'url': 'https://external-preview.redd.it/RWnBj-m9OL2YChixPfK99gwnogICJmHOW0j8MrU__kM.jpg?width=1080&crop=smart&auto=webp&s=fdcaff4d1690da57e03fe1a07d883f133433b1f9', 'width': 1080}], 'source': {'height': 1005, 'url': 'https://external-preview.redd.it/RWnBj-m9OL2YChixPfK99gwnogICJmHOW0j8MrU__kM.jpg?auto=webp&s=66674b5f2d6da0d8c880882badde2dbebd064191', 'width': 1920}, 'variants': {}}]} |
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🎙️ Looking for Beta Testers – Get 24 Hours of Free TTS Audio | 0 | I'm launching a new TTS (text-to-speech) service and I'm looking for a few early users to help test it out. If you're into AI voices, audio content, or just want to convert a lot of text to audio, this is a great chance to try it for free.
✅ Beta testers get **24 hours of audio generation** (no strings attached)
✅ Supports multiple voices and formats
✅ Ideal for podcasts, audiobooks, screenreaders, etc.
If you're interested, **DM me** and I'll get you set up with access. Feedback is optional but appreciated!
Thanks! 🙌 | 2025-06-11T01:48:43 | https://www.reddit.com/r/LocalLLaMA/comments/1l8gn0a/looking_for_beta_testers_get_24_hours_of_free_tts/ | mythicinfinity | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1l8gn0a | false | null | t3_1l8gn0a | /r/LocalLLaMA/comments/1l8gn0a/looking_for_beta_testers_get_24_hours_of_free_tts/ | false | false | self | 0 | null |
How does one get the new Qwen3 reranking models to work in llama.cpp? (GGUF) | 16 | The documentation isn’t great, and I haven’t been able to get it working with llama-server either. Anyone had any luck? | 2025-06-11T02:19:32 | https://www.reddit.com/r/LocalLLaMA/comments/1l8h95q/how_does_one_get_the_new_qwen3_reranking_models/ | 42GOLDSTANDARD42 | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1l8h95q | false | null | t3_1l8h95q | /r/LocalLLaMA/comments/1l8h95q/how_does_one_get_the_new_qwen3_reranking_models/ | false | false | self | 16 | null |
With an AI code execution agent, how should it approach sandboxing? | 2 | I'm working on an AI agent that can run and execute code. Currently the code (Python) is executed in a docker container with resource limits, and no direct filesystem access. The problem with this is that if I want to include specific tools or functions, (for instance, a module containing functions to send emails or other utilities for the LLM to use in its code), it is complicated by the sandbox. I could simply use `exec`, but that would worsen the already vulnerable project. I could also use a function wrapped with an API, but this also presents issues. Does anyone have any suggestions to solve this? | 2025-06-11T02:20:32 | https://www.reddit.com/r/LocalLLaMA/comments/1l8h9wa/with_an_ai_code_execution_agent_how_should_it/ | Pretend_Guava7322 | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1l8h9wa | false | null | t3_1l8h9wa | /r/LocalLLaMA/comments/1l8h9wa/with_an_ai_code_execution_agent_how_should_it/ | false | false | self | 2 | null |
Recommended cloud machines for DeepSeek R1? | 3 | I know, I know, we're in LocalLlama, but hear me out.
Given that it's a bit tricky to run a small datacenter with enough latest-gen VRAM at home, I'm looking for the next best option. Are there any good and trusted options you use to run it in cloud?
(Note: I understand there are ways to run DeepSeek at home on cheap-ish hardware, but I'd like it at the speed and responsiveness of the latest Nvidias.)
Things I'd like to see:
1. Reasonable cost + paying only when used rather than having an expensive machine running 24/7.
2. As much transparency and control over the machine and how it handles the models and data as possible. This is why we would ideally want to run it at home, is there a cloud provider that offers as close to at-home experience as possible?
I've been using Together AI so far for similar things, but I'd like to have more control over the machine rather than just trust they're not logging the data and they're giving me the model I want. Ideally, create a snapshot / docker image that would give me full control over what's going on, specify exact versions of the model and inference engine, possibly deploy custom code, and then have it spin up and spin down automatically when I need.
Anyone got any recommendations or experience to share? How much does your cloud setup cost you?
Thanks a lot! | 2025-06-11T02:42:09 | https://www.reddit.com/r/LocalLLaMA/comments/1l8hp5t/recommended_cloud_machines_for_deepseek_r1/ | lakySK | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1l8hp5t | false | null | t3_1l8hp5t | /r/LocalLLaMA/comments/1l8hp5t/recommended_cloud_machines_for_deepseek_r1/ | false | false | self | 3 | null |
Best local coding model | 1 | [removed] | 2025-06-11T03:03:15 | https://www.reddit.com/r/LocalLLaMA/comments/1l8i3w1/best_local_coding_model/ | FlowgrammerCrew | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1l8i3w1 | false | null | t3_1l8i3w1 | /r/LocalLLaMA/comments/1l8i3w1/best_local_coding_model/ | false | false | self | 1 | null |
Why are there drastic differences between deepseek r1 models on pocketpal? | 0 | 2025-06-11T03:13:07 | johncenaraper | i.redd.it | 1970-01-01T00:00:00 | 0 | {} | 1l8iahr | false | null | t3_1l8iahr | /r/LocalLLaMA/comments/1l8iahr/why_are_there_drastic_differences_between/ | false | false | 0 | {'enabled': True, 'images': [{'id': 'iokZiZC4sDGW8xS1VfV2qJJlm_Rol3l87iEXHASen8Q', 'resolutions': [{'height': 216, 'url': 'https://preview.redd.it/imv6t0wit76f1.jpeg?width=108&crop=smart&auto=webp&s=512cc06d96c3153034fc60223ea8741efaa01e8c', 'width': 108}, {'height': 432, 'url': 'https://preview.redd.it/imv6t0wit76f1.jpeg?width=216&crop=smart&auto=webp&s=d89da8205053e0b1c1fe41427dbc5f479a6a21dc', 'width': 216}, {'height': 640, 'url': 'https://preview.redd.it/imv6t0wit76f1.jpeg?width=320&crop=smart&auto=webp&s=b57b2057960ae48e56e339bed86449965e2f50ff', 'width': 320}, {'height': 1280, 'url': 'https://preview.redd.it/imv6t0wit76f1.jpeg?width=640&crop=smart&auto=webp&s=5bbadee3d1ea105bc55ab3b0d716dea4b2a6d8f4', 'width': 640}, {'height': 1920, 'url': 'https://preview.redd.it/imv6t0wit76f1.jpeg?width=960&crop=smart&auto=webp&s=eed15ed561375c86f8c38b68fb6f0b4219d09de6', 'width': 960}, {'height': 2160, 'url': 'https://preview.redd.it/imv6t0wit76f1.jpeg?width=1080&crop=smart&auto=webp&s=df269506558dff7c8c029a1ae2f7630567f65c72', 'width': 1080}], 'source': {'height': 2796, 'url': 'https://preview.redd.it/imv6t0wit76f1.jpeg?auto=webp&s=6853429e464612e1d6c41eb11ab69c30d1b37121', 'width': 1290}, 'variants': {}}]} |
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How do I make an LLM act more human. With imperfections, hesitation, natural pauses, shorter replies, etc.? | 49 | Hey all,
I've been trying to build a more human-like LLM. Not just smart, but emotionally and behaviorally human. I want it to **hesitate**, **think before responding**, sometimes reply in **shorter, more casual ways**, maybe **swear**, **joke**, or even get things a bit wrong like people do. Basically, feel like you're talking to a *real person*, not a perfectly optimized AI that responds with a whole fuckin essay every time.
No matter what I try, the responses always end up feeling **too polished**, **too long**, **too robotic**, or just fuckin off. I've tried prompting it to "act like a human," or "talk like a friend," but it still doesn't hit that natural vibe (I actually made a lot of very detailed prompts, but at the end it turns out ot be very bad).
Has anyone had luck making an LLM feel truly human in conversation? Like someone you'd text or talk to casually? Any tips on prompt engineering, fine-tuning, or even injecting behavioral randomness? Like really anything? | 2025-06-11T03:19:02 | https://www.reddit.com/r/LocalLLaMA/comments/1l8ieff/how_do_i_make_an_llm_act_more_human_with/ | PhraseProfessional54 | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1l8ieff | false | null | t3_1l8ieff | /r/LocalLLaMA/comments/1l8ieff/how_do_i_make_an_llm_act_more_human_with/ | false | false | self | 49 | null |
[Major Update] llmbasedos: Now Docker-first + bootable USB keys dropping soon | 1 | [removed] | 2025-06-11T03:39:38 | https://github.com/iluxu/llmbasedos | iluxu | github.com | 1970-01-01T00:00:00 | 0 | {} | 1l8is7a | false | null | t3_1l8is7a | /r/LocalLLaMA/comments/1l8is7a/major_update_llmbasedos_now_dockerfirst_bootable/ | false | false | 1 | {'enabled': False, 'images': [{'id': 'kB_Vi1_3pPRsyqzS1Yxtf7SHPxp3A7697x_Ykpj9E9o', 'resolutions': [{'height': 54, 'url': 'https://external-preview.redd.it/6zi9JfPwuwB-jmIB2j-2gdp6SuFZzhNzke_4CKW7VA8.jpg?width=108&crop=smart&auto=webp&s=49fe8a351350d91caf93790646c811c0ba4b9224', 'width': 108}, {'height': 108, 'url': 'https://external-preview.redd.it/6zi9JfPwuwB-jmIB2j-2gdp6SuFZzhNzke_4CKW7VA8.jpg?width=216&crop=smart&auto=webp&s=f9c3b44dfc507f1584b1bfedc8e6f23f47b03094', 'width': 216}, {'height': 160, 'url': 'https://external-preview.redd.it/6zi9JfPwuwB-jmIB2j-2gdp6SuFZzhNzke_4CKW7VA8.jpg?width=320&crop=smart&auto=webp&s=255118c49fc5a993bda1194f9266bafbacef5930', 'width': 320}, {'height': 320, 'url': 'https://external-preview.redd.it/6zi9JfPwuwB-jmIB2j-2gdp6SuFZzhNzke_4CKW7VA8.jpg?width=640&crop=smart&auto=webp&s=723cbcfcfc62518474a41c2dc7f16c98257a373e', 'width': 640}, {'height': 480, 'url': 'https://external-preview.redd.it/6zi9JfPwuwB-jmIB2j-2gdp6SuFZzhNzke_4CKW7VA8.jpg?width=960&crop=smart&auto=webp&s=387bb5ad5ad3519aee481c06acab84e946ca8ef9', 'width': 960}, {'height': 540, 'url': 'https://external-preview.redd.it/6zi9JfPwuwB-jmIB2j-2gdp6SuFZzhNzke_4CKW7VA8.jpg?width=1080&crop=smart&auto=webp&s=7e6b493f98d590bea6c9a84456978c7f9d406204', 'width': 1080}], 'source': {'height': 600, 'url': 'https://external-preview.redd.it/6zi9JfPwuwB-jmIB2j-2gdp6SuFZzhNzke_4CKW7VA8.jpg?auto=webp&s=f95a1eae25134af7636ef8cae0f71e9fb67d6a8d', 'width': 1200}, 'variants': {}}]} |
|
Best OS for a local AI server | 1 | [removed] | 2025-06-11T05:05:27 | https://www.reddit.com/r/LocalLLaMA/comments/1l8kaa6/best_os_for_a_local_ai_server/ | Impossible-Web-2782 | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1l8kaa6 | false | null | t3_1l8kaa6 | /r/LocalLLaMA/comments/1l8kaa6/best_os_for_a_local_ai_server/ | false | false | self | 1 | null |
Eye catching topic | 1 | [removed] | 2025-06-11T05:10:17 | https://www.reddit.com/r/LocalLLaMA/comments/1l8kczo/eye_catching_topic/ | Zucchini_Klutzy | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1l8kczo | false | null | t3_1l8kczo | /r/LocalLLaMA/comments/1l8kczo/eye_catching_topic/ | false | false | self | 1 | null |
NSFW image to text | 24 | Hi everyone,
I’m doing some research using disturbing images, and some of the images are being flagged as NSFW by openAi models and other models (i.e. grok, gemini, Claude).
Anyone have any indication of local (or server) models (preferably with API) with less filters that are mire ir less plug and play?
Thanks in advance! | 2025-06-11T05:45:13 | https://www.reddit.com/r/LocalLLaMA/comments/1l8kx53/nsfw_image_to_text/ | CarRepresentative843 | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1l8kx53 | false | null | t3_1l8kx53 | /r/LocalLLaMA/comments/1l8kx53/nsfw_image_to_text/ | false | false | nsfw | 24 | null |
What is the best set up for LLM and ai agent like crewai? | 1 | [removed] | 2025-06-11T06:40:59 | https://www.reddit.com/r/LocalLLaMA/comments/1l8lrjr/what_is_the_best_set_up_for_llm_and_ai_agent_like/ | Ill_Occasion_1537 | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1l8lrjr | false | null | t3_1l8lrjr | /r/LocalLLaMA/comments/1l8lrjr/what_is_the_best_set_up_for_llm_and_ai_agent_like/ | false | false | self | 1 | null |
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