# 量化benchmark ## Hunyuan-Instruct Hunyuan-Instruct的`BF16`、`FP8`、`INT4-GPTQ`、`INT4-AWQ`在`OlympiadBench`、`AIME 2024`、`DROP`、`GPQA-Diamond`上的评测结果如下： ```{eval-rst} .. table:: :align: center :name: table-Hunyuan-Instruct-performance +-----------------------+--------------+---------+---------+---------+-----------+ | Model | Quantization | CEVAL | MMLU | GSM8K | HUMANEVAL | +=======================+==============+=========+=========+=========+===========+ | Hunyuan-A13B-Instruct | BF16 | 82.70 | 87.30 | 91.10 | 71.20 | + +--------------+---------+---------+---------+-----------+ | | FP8-Static | 83.00 | 86.70 | 91.10 | - | + +--------------+---------+---------+---------+-----------+ | | INT4-GPTQ | 82.70 | 86.70 | 91.10 | - | + +--------------+---------+---------+---------+-----------+ | | INT4-AWQ | 82.60 | 85.60 | 91.00 | - | +-----------------------+--------------+---------+---------+---------+-----------+ | Hunyuan-7B-Instruct | BF16 | 76.50 | 81.10 | 85.90 | 60.10 | + +--------------+---------+---------+---------+-----------+ | | FP8-Static | 76.60 | 80.90 | 86.00 | 60.10 | + +--------------+---------+---------+---------+-----------+ | | INT4-GPTQ | 76.20 | 81.00 | 85.70 | 60.00 | + +--------------+---------+---------+---------+-----------+ | | INT4-AWQ | 76.40 | 80.90 | 85.90 | 60.10 | +-----------------------+--------------+---------+---------+---------+-----------+ | Hunyuan-4B-Instruct | BF16 | 73.10 | 78.30 | 78.20 | 61.10 | + +--------------+---------+---------+---------+-----------+ | | FP8-Static | 73.10 | 76.60 | 78.30 | 60.20 | + +--------------+---------+---------+---------+-----------+ | | INT4-GPTQ | 72.90 | - | 78.10 | 58.10 | + +--------------+---------+---------+---------+-----------+ | | INT4-AWQ | 72.80 | - | 78.20 | - | +-----------------------+--------------+---------+---------+---------+-----------+ | Hunyuan-1.8B-Instruct | BF16 | 63.40 | 56.70 | 76.70 | 47.20 | + +--------------+---------+---------+---------+-----------+ | | FP8-Static | 62.50 | 55.20 | 75.10 | 47.70 | + +--------------+---------+---------+---------+-----------+ | | INT4-GPTQ | 60.90 | - | 73.00 | 44.40 | + +--------------+---------+---------+---------+-----------+ | | INT4-AWQ | 61.70 | - | 71.70 | 43.60 | +-----------------------+--------------+---------+---------+---------+-----------+ | Hunyuan-0.5B-Instruct | BF16 | 29.60 | 17.20 | 52.80 | 23.30 | + +--------------+---------+---------+---------+-----------+ | | FP8-Static | 29.60 | 17.20 | 51.60 | 22.50 | + +--------------+---------+---------+---------+-----------+ | | INT4-GPTQ | 26.80 | - | 50.90 | 23.30 | + +--------------+---------+---------+---------+-----------+ | | INT4-AWQ | 26.30 | - | 48.90 | 23.30 | +-----------------------+--------------+---------+---------+---------+-----------+ ``` ## Qwen3 Qwen3系列模型的`BF16`、`FP8-Static`、`FP8-Dynamic`、`INT4-GPTQ`、`INT4-AWQ`在`CEVAL`、`MMLU`、`GSM8K`、`HUMANEVAL`上的评测结果如下： ```{eval-rst} .. table:: :align: center :name: table-qwen3-performance +-------------------+--------------+---------+---------+---------+-----------+ | Model | Quantization | CEVAL | MMLU | GSM8K | HUMANEVAL | +===================+==============+=========+=========+=========+===========+ | Qwen3-0.6B | BF16 | 45.84 | 47.21 | 42.99 | 19.51 | + +--------------+---------+---------+---------+-----------+ | | FP8-Static | 45.99 | 46.87 | 38.06 | 18.90 | + +--------------+---------+---------+---------+-----------+ | | FP8-Dynamic | 45.99 | 46.93 | 38.29 | 20.73 | + +--------------+---------+---------+---------+-----------+ | | INT8-Dynamic | 45.17 | 46.95 | 41.17 | 21.34 | +-------------------+--------------+---------+---------+---------+-----------+ | Qwen3-1.7B | BF16 | 60.33 | 59.77 | 68.69 | 40.85 | + +--------------+---------+---------+---------+-----------+ | | FP8-Static | 61.07 | 59.39 | 68.01 | 38.41 | + +--------------+---------+---------+---------+-----------+ | | FP8-Dynamic | 60.77 | 59.88 | 67.10 | 34.76 | + +--------------+---------+---------+---------+-----------+ | | INT8-Dynamic | 60.25 | 59.80 | 68.54 | 41.46 | + +--------------+---------+---------+---------+-----------+ | | INT4-GPTQ | 57.50 | 56.93 | - | - | + +--------------+---------+---------+---------+-----------+ | | INT4-AWQ | 59.06 | 56.86 | - | - | +-------------------+--------------+---------+---------+---------+-----------+ | Qwen3-4B | BF16 | 72.66 | 69.99 | 85.37 | 72.56 | + +--------------+---------+---------+---------+-----------+ | | FP8-Static | 72.14 | 69.93 | 83.70 | 73.17 | + +--------------+---------+---------+---------+-----------+ | | FP8-Dynamic | 70.80 | 70.08 | 83.40 | 69.51 | + +--------------+---------+---------+---------+-----------+ | | INT8-Dynamic | 72.21 | 69.47 | 85.75 | 66.46 | + +--------------+---------+---------+---------+-----------+ | | INT4-GPTQ | 70.06 | 68.59 | 81.65 | - | + +--------------+---------+---------+---------+-----------+ | | INT4-AWQ | 70.36 | 67.62 | 80.59 | - | +-------------------+--------------+---------+---------+---------+-----------+ | Qwen3-8B | BF16 | 79.27 | 74.78 | 87.79 | 63.41 | + +--------------+---------+---------+---------+-----------+ | | FP8-Static | 78.23 | 74.79 | 86.96 | 62.20 | + +--------------+---------+---------+---------+-----------+ | | FP8-Dynamic | 78.45 | 74.75 | 87.64 | 62.80 | + +--------------+---------+---------+---------+-----------+ | | INT8-Dynamic | 78.01 | 74.84 | 86.96 | 67.07 | + +--------------+---------+---------+---------+-----------+ | | INT4-GPTQ | 77.19 | 73.26 | 86.43 | 62.20 | + +--------------+---------+---------+---------+-----------+ | | INT4-AWQ | 76.15 | 73.59 | 86.96 | 63.41 | +-------------------+--------------+---------+---------+---------+-----------+ | Qwen3-14B | BF16 | 83.06 | 78.90 | 88.40 | 55.49 | + +--------------+---------+---------+---------+-----------+ | | FP8-Static | 82.62 | 78.57 | 89.46 | 57.32 | + +--------------+---------+---------+---------+-----------+ | | FP8-Dynamic | 82.24 | 78.92 | 88.32 | 52.44 | + +--------------+---------+---------+---------+-----------+ | | INT8-Dynamic | 81.87 | 78.13 | 86.28 | 56.10 | + +--------------+---------+---------+---------+-----------+ | | INT4-GPTQ | 81.05 | 78.02 | 87.34 | 57.93 | + +--------------+---------+---------+---------+-----------+ | | INT4-AWQ | 82.02 | 77.68 | 84.23 | 61.59 | +-------------------+--------------+---------+---------+---------+-----------+ | Qwen3-30B-A3B | BF16 | 83.66 | 79.36 | 89.99 | 31.71 | + +--------------+---------+---------+---------+-----------+ | | FP8-Static | 83.95 | 79.47 | 89.01 | 31.10 | + +--------------+---------+---------+---------+-----------+ | | FP8-Dynamic | 84.10 | 79.40 | 89.16 | 32.93 | + +--------------+---------+---------+---------+-----------+ | | INT8-Dynamic | 83.36 | 79.48 | 89.16 | 34.15 | +-------------------+--------------+---------+---------+---------+-----------+ | Qwen3-32B | BF16 | 86.55 | 82.00 | 74.53 | 37.80 | + +--------------+---------+---------+---------+-----------+ | | FP8-Static | 86.92 | 81.78 | 70.20 | 39.63 | + +--------------+---------+---------+---------+-----------+ | | FP8-Dynamic | 86.55 | 81.89 | 70.43 | 38.41 | + +--------------+---------+---------+---------+-----------+ | | INT4-GPTQ | 86.18 | 81.01 | - | 43.29 | + +--------------+---------+---------+---------+-----------+ | | INT4-AWQ | 86.18 | 81.54 | - | 36.59 | +-------------------+--------------+---------+---------+---------+-----------+ | Qwen3-235B-A22B | BF16 | 89.60 | 86.28 | 85.29 | 27.44 | + +--------------+---------+---------+---------+-----------+ | | FP8-Static | 89.67 | 86.19 | 86.96 | 27.44 | + +--------------+---------+---------+---------+-----------+ | | FP8-Dynamic | 89.67 | 86.18 | 85.22 | 28.05 | + +--------------+---------+---------+---------+-----------+ | | INT8-Dynamic | 88.93 | 86.20 | 86.20 | 23.78 | +-------------------+--------------+---------+---------+---------+-----------+ | QwQ-32B | BF16 | 85.74 | 82.03 | 73.31 | 42.68 | + +--------------+---------+---------+---------+-----------+ | | FP8-Static | 85.44 | 81.91 | 75.36 | 42.68 | + +--------------+---------+---------+---------+-----------+ | | FP8-Dynamic | 85.07 | 81.93 | 75.66 | 42.07 | + +--------------+---------+---------+---------+-----------+ | | INT8-Dynamic | 86.40 | 81.97 | 74.37 | 45.73 | + +--------------+---------+---------+---------+-----------+ | | INT4-GPTQ | 84.03 | 81.26 | 68.23 | 45.73 | + +--------------+---------+---------+---------+-----------+ | | INT4-AWQ | 83.58 | 81.01 | 68.69 | 43.29 | +-------------------+--------------+---------+---------+---------+-----------+ ``` ## Qwen2.5VL Qwen2.5VL系列模型的`BF16`、`FP8-Static`、`FP8-Dynamic`、`FP8-Static-ViT`、`FP8-Dynamic-ViT`、`INT4-GPTQ`、`INT4-AWQ`在`MMMU_VAL`、`DocVQA_VAL`、`ChartQA_TEST`上的评测结果如下： ```{eval-rst} .. table:: :align: center :name: table-qwen2.5vl-performance +-------------------+------------------+----------+------------+--------------+ | Model | Quantization | MMMU_VAL | DocVQA_VAL | ChartQA_TEST | +===================+==================+==========+============+==============+ | Qwen2.5VL-3B | BF16 | 47.11 | 78.57 | 80.32 | + +------------------+----------+------------+--------------+ | | FP8-Static | 47.33 | 79.34 | 79.68 | + +------------------+----------+------------+--------------+ | | FP8-Dynamic | 47.00 | 78.92 | 79.60 | + +------------------+----------+------------+--------------+ | | FP8-Static-ViT | 45.56 | 79.36 | 80.16 | + +------------------+----------+------------+--------------+ | | INT8-Dynamic-ViT | 46.67 | 79.26 | 79.84 | + +------------------+----------+------------+--------------+ | | INT4-GPTQ | 46.56 | 77.20 | 78.96 | + +------------------+----------+------------+--------------+ | | INT4-AWQ | 45.78 | - | 79.60 | +-------------------+------------------+----------+------------+--------------+ | Qwen2.5VL-7B | BF16 | 45.44 | 89.71 | 84.64 | | +------------------+----------+------------+--------------+ | | FP8-Static | 47.00 | 89.83 | 85.92 | + +------------------+----------+------------+--------------+ | | FP8-Dynamic | 47.22 | 89.80 | 88.64 | + +------------------+----------+------------+--------------+ | | FP8-Static-ViT | 47.00 | 89.85 | 86.88 | + +------------------+----------+------------+--------------+ | | INT8-Dynamic-ViT | 46.44 | 89.68 | 88.72 | + +------------------+----------+------------+--------------+ | | INT4-GPTQ | 46.67 | 90.45 | - | + +------------------+----------+------------+--------------+ | | INT4-AWQ | 45.67 | 89.28 | - | +-------------------+------------------+----------+------------+--------------+ | Qwen2.5VL-32B | BF16 | 57.00 | 90.03 | - | | +------------------+----------+------------+--------------+ | | FP8-Static | 57.00 | 89.88 | - | + +------------------+----------+------------+--------------+ | | FP8-Dynamic | 56.44 | 89.88 | - | + +------------------+----------+------------+--------------+ | | FP8-Static-ViT | 56.33 | 89.92 | - | + +------------------+----------+------------+--------------+ | | INT8-Dynamic-ViT | 57.22 | 89.88 | - | + +------------------+----------+------------+--------------+ | | INT4-GPTQ | 55.22 | 89.80 | - | + +------------------+----------+------------+--------------+ | | INT4-AWQ | 55.22 | 90.30 | - | +-------------------+------------------+----------+------------+--------------+ | Qwen2.5VL-72B | BF16 | 58.78 | 94.39 | 85.60 | | +------------------+----------+------------+--------------+ | | FP8-Static | 57.89 | 94.41 | 85.84 | + +------------------+----------+------------+--------------+ | | FP8-Dynamic | 58.67 | 94.38 | 85.60 | + +------------------+----------+------------+--------------+ | | FP8-Static-ViT | 57.44 | 94.48 | 85.84 | + +------------------+----------+------------+--------------+ | | INT8-Dynamic-ViT | 58.22 | 94.47 | 86.00 | + +------------------+----------+------------+--------------+ | | INT4-GPTQ | 57.56 | 94.46 | 86.48 | + +------------------+----------+------------+--------------+ | | INT4-AWQ | 58.78 | 94.19 | 87.28 | +-------------------+------------------+----------+------------+--------------+ ``` ## DeepSeek-R1-0528 DeepSeek-R1-0528模型的`FP8-Block-Wise`、`W4A8-FP8`在`GPQA Diamond`、`AIME 2024`、`SimpleQA`、`LiveCodeBench`上的评测结果如下： ```{eval-rst} .. table:: :align: center :name: table-DeepSeek-R1-0528-performance +-----------------------+----------------+--------------+-----------+----------+---------------+ | Model | Quantization | GPQA Diamond | AIME 2024 | SimpleQA | LiveCodeBench | +=======================+================+==============+===========+==========+===============+ | DeepSeek-R1-0528 | FP8-Block-Wise | 78.28 | 88.67 | 27.80 | 77.1 | + +----------------+--------------+-----------+----------+---------------+ | | W4A8-FP8 | 77.37 | 88.67 | 26.83 | 78.86 | +-----------------------+----------------+--------------+-----------+----------+---------------+ ``` ## Seed-OSS-36B-Instruct Seed-OSS-36B-Instruct模型的`FP8-Static`、`FP8-Dynamic`在`CEVAL`、`MMLU`、`GSM8K`、`HUMANEVAL`上的评测结果如下： ```{eval-rst} .. table:: :align: center :name: table-seed-oss-36b-performance +-------------------------+----------------+---------+--------+----------------+------------------+-------------+ | Model | Quantization | CEVAL | MMLU | GSM8K-strict | GSM8K-flexible | HUMANEVAL | +=========================+================+=========+========+================+==================+=============+ | Seed-OSS-36B-Instruct | BF16 | 88.19 | 82.97 | 70.36 | 97.12 | 87.20 | + +----------------+---------+--------+----------------+------------------+-------------+ | | FP8-Static | 87.82 | 82.79 | 74.75 | 96.51 | 86.59 | + +----------------+---------+--------+----------------+------------------+-------------+ | | FP8-Dynamic | 87.82 | 82.64 | 74.15 | 96.89 | 87.20 | +-------------------------+----------------+---------+--------+----------------+------------------+-------------+ ``` 该数据使用[lm-eval](https://github.com/EleutherAI/lm-evaluation-harness)工具评测，注意需要设置`--gen_kwargs max_gen_toks`防止思考内容过长被截断。 ## GLM-4.6 GLM-4.6模型的`FP8-Static`、`FP8-Dynamic`在`CEVAL`、`GSM8K`、`HUMANEVAL`上的评测结果如下： ```{eval-rst} .. table:: :align: center :name: glm-4.6-performance +-------------------+--------------+---------+---------+-----------+ | Model | Quantization | CEVAL | GSM8K | HUMANEVAL | +===================+==============+=========+=========+===========+ | GLM-4.6 | BF16 | 82.6 | 93.71 | 73.78 | + +--------------+---------+---------+-----------+ | | FP8-Static | 83.14 | 93.86 | 66.46 | + +--------------+---------+---------+-----------+ | | FP8-Dynamic | 82.91 | 93.71 | 63.41 | +-------------------+--------------+---------+---------+-----------+ ``` ## 其他模型 其他模型的`BF16`、`FP8-Static`、`FP8-Dynamic`、`INT4-GPTQ`、`INT4-AWQ`在`CEVAL`、`MMLU`、`GSM8K`上的评测结果如下： ```{eval-rst} .. table:: :align: center :name: table-other-performance +-------------------------------+--------------+---------+---------+---------+ | Model | Quantization | CEVAL | MMLU | GSM8K | +===============================+==============+=========+=========+=========+ | Qwen2.5-1.5B-Instruct | BF16 | 67.01 | 60.05 | 54.28 | + +--------------+---------+---------+---------+ | | FP8-Static | 66.27 | 60.23 | - | + +--------------+---------+---------+---------+ | | FP8-Dynamic | 66.79 | 60.08 | 51.71 | +-------------------------------+--------------+---------+---------+---------+ | Qwen2.5-7B-Instruct | BF16 | 81.20 | 74.55 | 79.98 | + +--------------+---------+---------+---------+ | | FP8-Static | 81.13 | 74.03 | 79.30 | + +--------------+---------+---------+---------+ | | FP8-Dynamic | 80.31 | 74.07 | 79.00 | + +--------------+---------+---------+---------+ | | INT4-GPTQ | 79.05 | 73.05 | 74.75 | + +--------------+---------+---------+---------+ | | INT4-AWQ | 79.35 | 73.22 | 79.38 | +-------------------------------+--------------+---------+---------+---------+ | Qwen2.5-32B-Instruct | BF16 | 87.30 | 83.21 | 81.73 | + +--------------+---------+---------+---------+ | | FP8-Static | 87.59 | 83.08 | 81.58 | + +--------------+---------+---------+---------+ | | FP8-Dynamic | 87.30 | 83.04 | 81.58 | + +--------------+---------+---------+---------+ | | INT4-GPTQ | 86.70 | 82.45 | 82.03 | + +--------------+---------+---------+---------+ | | INT4-AWQ | 87.00 | 82.64 | - | +-------------------------------+--------------+---------+---------+---------+ | DeepSeek-R1-Distill-Qwen-1.5B | BF16 | 37.22 | 36.63 | 67.02 | + +--------------+---------+---------+---------+ | | FP8-Static | 35.44 | 37.41 | - | + +--------------+---------+---------+---------+ | | FP8-Dynamic | 35.96 | 36.12 | 64.75 | +-------------------------------+--------------+---------+---------+---------+ | DeepSeek-R1-Distill-Qwen-7B | BF16 | 53.49 | 53.80 | 75.74 | + +--------------+---------+---------+---------+ | | FP8-Static | 53.57 | 54.17 | 76.19 | + +--------------+---------+---------+---------+ | | FP8-Dynamic | 52.97 | 54.13 | 74.15 | + +--------------+---------+---------+---------+ | | INT4-GPTQ | 51.86 | 52.44 | 75.89 | + +--------------+---------+---------+---------+ | | INT4-AWQ | 53.49 | 53.70 | - | +-------------------------------+--------------+---------+---------+---------+ | DeepSeek-R1-Distill-Qwen-14B | BF16 | 77.71 | 74.28 | 85.67 | + +--------------+---------+---------+---------+ | | FP8-Static | 77.56 | 74.66 | 86.73 | + +--------------+---------+---------+---------+ | | FP8-Dynamic | 76.82 | 74.63 | 87.11 | + +--------------+---------+---------+---------+ | | INT4-GPTQ | 74.29 | 72.37 | 84.61 | + +--------------+---------+---------+---------+ | | INT4-AWQ | 74.81 | 73.00 | 86.05 | +-------------------------------+--------------+---------+---------+---------+ | DeepSeek-R1-Distill-Qwen-32B | BF16 | 84.18 | 80.89 | 87.41 | + +--------------+---------+---------+---------+ | | FP8-Static | 83.43 | 80.90 | 87.57 | + +--------------+---------+---------+---------+ | | FP8-Dynamic | 83.73 | 81.10 | 86.43 | + +--------------+---------+---------+---------+ | | INT4-GPTQ | 84.10 | 79.80 | 86.73 | + +--------------+---------+---------+---------+ | | INT4-AWQ | 82.84 | 80.15 | 87.19 | +-------------------------------+--------------+---------+---------+---------+ ``` ## INT4-GPTAQ INT4-GPTAQ在`GSM8K`、`HUMANEVAL`、`GPQA Diamond`上的评测结果如下： ```{eval-rst} .. table:: :align: center :name: table-INT4-GPTAQ-performance +-----------+--------------+-------+-----------+--------------+ | Model | Quantization | GSM8K | HUMANEVAL | GPQA Diamond | +===========+==============+=======+===========+==============+ | Qwen3-4B | BF16 | 85.37 | 72.56 | 37.88 | + +--------------+-------+-----------+--------------+ | | INT4-GPTQ | 81.65 | 61.59 | 35.35 | + +--------------+-------+-----------+--------------+ | | INT4-GPTAQ | 82.56 | 64.02 | 39.39 | +-----------+--------------+-------+-----------+--------------+ | Qwen3-8B | BF16 | 87.79 | 63.41 | 32.32 | + +--------------+-------+-----------+--------------+ | | INT4-GPTQ | 86.43 | 62.20 | 34.85 | + +--------------+-------+-----------+--------------+ | | INT4-GPTAQ | 86.66 | 64.02 | 33.33 | +-----------+--------------+-------+-----------+--------------+ | Qwen3-32B | BF16 | 74.53 | 37.80 | 40.40 | + +--------------+-------+-----------+--------------+ | | INT4-GPTQ | 65.58 | 43.29 | 40.40 | + +--------------+-------+-----------+--------------+ | | INT4-GPTAQ | 69.52 | 37.20 | - | +-----------+--------------+-------+-----------+--------------+ ``` ## NVFP4 NVFP4在`GSM8K`、`MMLU`、`GPQA Diamond`上的评测结果如下： ```{eval-rst} .. table:: :align: center :name: table-NVFP4-performance +-----------------+--------------+-------+-------+--------------+ | Model | Quantization | GSM8K | MMLU | GPQA Diamond | +=================+==============+=======+=======+==============+ | Qwen3-32B | BF16 | 67.06 | 81.72 | 54.04 | + +--------------+-------+-------+--------------+ | | NVFP4 | 69.87 | 80.74 | 56.06 | +-----------------+--------------+-------+-------+--------------+ | Qwen3-235B-A22B | BF16 | 96.63 | 62.73 | 60.60 | + +--------------+-------+-------+--------------+ | | NVFP4 | 96.17 | 62.09 | 60.10 | +-----------------+--------------+-------+-------+--------------+ ``` ## Qwen3VL Qwen3VL系列模型的`BF16`、`FP8-Static`、`FP8-Dynamic`在`MMMU_VAL`、`DocVQA_VAL`、`ChartQA_TEST`上的评测结果如下： ```{eval-rst} .. table:: :align: center :name: table-qwen3vl-performance +---------------------------+------------------+----------+------------+--------------+ | Model | Quantization | MMMU_VAL | DocVQA_VAL | ChartQA_TEST | +===========================+==================+==========+============+==============+ | Qwen3-VL-32B-Instruct | BF16 | 60.11 | 96.08 | 94.64 | + +------------------+----------+------------+--------------+ | | FP8-Static | 61.22 | 96.00 | 94.64 | + +------------------+----------+------------+--------------+ | | FP8-Dynamic | 60.78 | 96.19 | 94.72 | +---------------------------+------------------+----------+------------+--------------+ | Qwen3-VL-30B-A3B-Instruct | BF16 | 50.44 | 95.28 | 95.36 | + +------------------+----------+------------+--------------+ | | FP8-Dynamic | 50.67 | 95.25 | 95.20 | +---------------------------+------------------+----------+------------+--------------+ ``` FP8-Dynamic采用Block-wise的量化，启动命令：python3 tools/fp8_quant_blockwise.py --block_size --input_path --output_path ## Qwen3-Omni **Qwen3-Omni Text -> Text Benchmark** Qwen3-Omni模型的`BF16`、`FP8-Static`、`FP8-Dynamic`在`aime25`、`gpqa_diamond`、`mmlu_redux`上的评测结果如下： ```{eval-rst} .. table:: :align: center :name: table-qwen3-omni-performance +-----------------------------+----------------+----------+--------------+------------+ | Model | Quantization | aime25 | gpqa_diamond | mmlu_redux | +=============================+================+==========+==============+============+ | Qwen3-Omni-30B-A3B-Instruct | BF16 | 73.32 | 56.77 | 88.09 | + +----------------+----------+--------------+------------+ | | FP8-Static | 71.33 | 56.57 | 87.91 | + +----------------+----------+--------------+------------+ | | FP8-Dynamic | 73.33 | 55.15 | 88.07 | +-----------------------------+----------------+----------+--------------+------------+ ```