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README.md
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### Reproduction
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The results can be reproduced using vLLM emulation docker: rocmshared/pytorch:vllm-gfx950-mxfp4-mxfp6-v3
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The results of AIME24, MATH-500, and GPQA Diamond, were obtained using [vLLM](https://docs.vllm.ai/en/latest/) while GSM8K was obtained using [SGLang](https://docs.sglang.ai/). For AIME24, MATH-500, and GPQA Diamond, we took 10 rounds with different random seeds for reliable performance estimation.
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### Reproduction
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The results can be reproduced using vLLM emulation docker: `rocmshared/pytorch:vllm-gfx950-mxfp4-mxfp6-v3`.
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The results of AIME24, MATH-500, and GPQA Diamond, were obtained using [vLLM](https://docs.vllm.ai/en/latest/) while GSM8K was obtained using [SGLang](https://docs.sglang.ai/). For AIME24, MATH-500, and GPQA Diamond, we took 10 rounds with different random seeds for reliable performance estimation.
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```
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