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---
tags:
- fp8
- vllm
---
# Mixtral-8x22B-Instruct-v0.1-FP8
## Model Overview
Mixtral-8x22B-Instruct-v0.1 quantized to FP8 weights and activations using per-tensor quantization, ready for inference with vLLM >= 0.5.0.
## Usage and Creation
Produced using [AutoFP8 with calibration samples from ultrachat](https://github.com/neuralmagic/AutoFP8/blob/147fa4d9e1a90ef8a93f96fc7d9c33056ddc017a/example_dataset.py).
## Evaluation
### Open LLM Leaderboard evaluation scores
| | Meta-Llama-3-70B-Instruct | Meta-Llama-3-70B-Instruct-FP8<br>(this model) |
| :------------------: | :----------------------: | :------------------------------------------------: |
| arc-c<br>25-shot | 71.58 | 72.09 |
| hellaswag<br>10-shot | 86.94 | 86.83 |
| mmlu<br>5-shot | 83.97 | 84.06 |
| truthfulqa<br>0-shot | 66.98 | 66.95 |
| winogrande<br>5-shot | 82.79 | 83.18 |
| gsm8k<br>5-shot | 87.56 | 88.93 |
| **Average<br>Accuracy** | **79.97** | **80.34** |
| **Recovery** | **100%** | **100.46%** |
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