---
license: other
base_model: MiniMaxAI/MiniMax-M3
pipeline_tag: image-text-to-text
library_name: transformers
tags:
- minimax-m3
- fp8
- compressed-tensors
- llm-compressor
- vllm
- rocm
- conversational
- image-text-to-text
---

# MiniMax-M3-FP8-dynamic

## Model Overview

This model is an FP8 dynamic quantized version of [MiniMaxAI/MiniMax-M3](https://huggingface.co/MiniMaxAI/MiniMax-M3).

- Base model: `MiniMaxAI/MiniMax-M3`
- Optimization: FP8 dynamic quantization
- Format: safetensors / compressed-tensors
- Validated runtime: vLLM OpenAI-compatible server
- Tested hardware: AMD MI350, tensor parallel size 8

MiniMax-M3 is a native multimodal MoE model. The original model card describes it as a ~428B parameter model with ~23B activated parameters and 1M context support.

## License

This quantized checkpoint follows the license terms of the base model, [MiniMaxAI/MiniMax-M3](https://huggingface.co/MiniMaxAI/MiniMax-M3). The Hugging Face model-card metadata uses `license: other` because the MiniMax community license is not one of the Hub's enumerated license identifiers.

## Model Optimizations

This checkpoint uses FP8 dynamic quantization to reduce memory and disk requirements while preserving model quality. Validation below compares this quantized checkpoint against the BF16 `MiniMaxAI/MiniMax-M3` baseline.

## Evaluation

The model was evaluated against BF16 `MiniMaxAI/MiniMax-M3`. Scores are averaged across seeds.

| Benchmark | MiniMaxAI/MiniMax-M3 | EmbeddedLLM/MiniMax-M3-FP8-dynamic | Recovery (%) |
|---|---:|---:|---:|
| GSM8k Platinum | 95.81 | 95.92 | 100.12 |
| IfEval | 80.65 | 79.42 | 98.47 |
| AIME 2025 | 20.83 | 19.17 | 92.00 |
| GPQA diamond | 77.78 | 77.95 | 100.22 |
| Math 500 | 81.20 | 79.93 | 98.44 |
| Lcb Codegeneration V6 | 37.14 | 35.62 | 95.90 |
| MMLU Pro Chat | 79.85 | 79.62 | 99.72 |

## Evaluation Setup

- Standard seeds: `42, 1234, 4158`
- AIME 2025 seeds: `42, 1234, 4158, 5322, 1356, 9843, 3344, 5678`
- GSM8K Platinum cap: `max_gen_toks=64000`
- IFEval, AIME, GPQA, Math 500, MMLU Pro Chat cap: `max_gen_toks=4096`
- LiveCodeBench v6 cap: `max_gen_toks=2048`
- MiniMax thinking mode: disabled
- Runners: lm-eval harness and lighteval through LiteLLM endpoint mode