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| title: README | |
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| # Software-Delivered AI Inference | |
| Neural Magic helps developers in accelerating deep learning performance using automated model sparsification technologies and inference engines. | |
| Download our sparsity-aware inference engines and open source tools for fast model inference. | |
| * [nm-vllm](https://github.com/neuralmagic/nm-vllm): A high-throughput and memory-efficient inference engine for LLMs, incorporating the latest LLM optimizations like quantization and sparsity | |
| * [DeepSparse](https://github.com/neuralmagic/deepsparse): Inference runtime offering GPU-class performance on CPUs and APIs to integrate ML into your application | |
| * [SparseML](https://github.com/neuralmagic/sparseml): Libraries for applying sparsification recipes to neural networks with a few lines of code, enabling faster and smaller models | |
| * [SparseZoo](https://sparsezoo.neuralmagic.com/): Neural network model repository for highly sparse and sparse-quantized models with matching sparsification recipes | |