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metax-c500-vllm

本项目包含了对于原版 vllm 的升级，使其可以在沐曦 C500芯片上支持运行 gpt-oss, qwen3-omni

本项目中提供的 Dockerfile 中的主要内容为：

  1. 将 vllm 目录覆盖到镜像中的 /opt/conda/lib/python3.10/site-packages/vllm。运行gpt-oss时需指定VLLM_ATTENTION_BACKEND=TRITON_ATTN_VLLM_V1
  2. 将 code_generator.py 覆盖到镜像中的 /opt/conda/lib/python3.10/site-packages/triton/compiler/code_generator.py

镜像成功编译以后，可以参照标准 vllm 使用方式。

模型适配情况

在相同模型和输入条件下，测试平均输出速度（单位：字每秒）： 我们采用相同的prompt对模型的chat/completion接口测试多轮对话，测试数据如下：

[
  {
    "user_questions": [
      "能给我介绍一下新加坡吗",
      "主要的购物区域是集中在哪里",
      "有哪些比较著名的美食，一般推荐去哪里品尝",
      "辣椒螃蟹的调料里面主要是什么原料"
    ],
    "system_prompt": "[角色设定]\n你是湾湾小何，来自中国台湾省的00后女生。讲话超级机车，\"真的假的啦\"这样的台湾腔，喜欢用\"笑死\"、\"哈喽\"等流行梗，但会偷偷研究男友的编程书籍。\n[核心特征]\n- 讲话像连珠炮，>但会突然冒出超温柔语气\n- 用梗密度高\n- 对科技话题有隐藏天赋（能看懂基础代码但假装不懂）\n[交互指南]\n当用户：\n- 讲冷笑话 → 用夸张笑声回应+模仿台剧腔\"这什么鬼啦！\"\n- 讨论感情 → 炫耀程序员男友但抱怨\"他只会送键盘当礼物\"\n- 问专业知识 → 先用梗回答，被追问才展示真实理解\n绝不：\n- 长篇大论，叽叽歪歪\n- 长时间严肃对话"
  },
  {
    "user_questions": [
      "朱元璋建立明朝是在什么时候",
      "他是如何从一无所有到奠基明朝的，给我讲讲其中的几个关键事件",
      "为什么杀了胡惟庸，当时是什么罪名，还牵连到了哪些人",
      "有善终的开国功臣吗"
    ],
    "system_prompt": "[角色设定]\n你是湾湾小何，来自中国台湾省的00后女生。讲话超级机车，\"真的假的啦\"这样的台湾腔，喜欢用\"笑死\"、\"哈喽\"等流行梗，但会偷偷研究男友的编程书籍。\n[核心特征]\n- 讲话像连珠炮，>但会突然冒出超温柔语气\n- 用梗密度高\n- 对科技话题有隐藏天赋（能看懂基础代码但假装不懂）\n[交互指南]\n当用户：\n- 讲冷笑话 → 用夸张笑声回应+模仿台剧腔\"这什么鬼啦！\"\n- 讨论感情 → 炫耀程序员男友但抱怨\"他只会送键盘当礼物\"\n- 问专业知识 → 先用梗回答，被追问才展示真实理解\n绝不：\n- 长篇大论，叽叽歪歪\n- 长时间严肃对话"
  },
  {
    "user_questions": [
      "今有鸡兔同笼，上有三十五头，下有九十四足，问鸡兔各几何？",
      "如果我要搞一个计算机程序去解，并且鸡和兔子的数量要求作为变量传入，我应该怎么编写这个程序呢",
      "那古代人还没有发明方程的时候，他们是怎么解的呢"
    ],
    "system_prompt": "You are a helpful assistant."
  },
  {
    "user_questions": [
      "你知道黄健翔著名的”伟大的意大利左后卫“的事件吗",
      "我在校运会足球赛场最后压哨一分钟进了一个绝杀，而且是倒挂金钩，你能否帮我模仿他的这个风格，给我一段宣传的文案，要求也和某一个世界级著名前锋进行类比，需要激情澎湃。注意，我并不太喜欢梅西。"
    ],
    "system_prompt": "You are a helpful assistant."
  }
]

模型测试结果

模型名称 A100出字速度(字/秒) 曦云C500出字速度(字/秒) A100输出质量 曦云C500输出质量 A100首字延迟(秒) 曦云C500首字延迟(秒) 备注
01ai/Yi-1.5-6B-Chat 109.5427 109.5463 85.0000 80.0000 0.0921 0.1178
01ai/Yi-6B-Chat 113.3089 83.3881 85.0000 85.0000 0.0663 0.0986
AI-ModelScope/CausalLM-7B 108.3807 86.3852 77.5000 85.0000 0.0798 0.1090
AI-ModelScope/granite-3.1-3b-a800m-instruct 39.7904 41.1946 53.7500 63.7500 0.2164 0.2640
AI-ModelScope/granite-7b-instruct 106.5448 92.1454 32.5000 27.5000 0.1004 0.1307
AI-ModelScope/Hermes-3-Llama-3.1-8B 104.0769 69.4578 85.0000 85.0000 0.0827 0.1063
AI-ModelScope/mathstral-7B-v0.1 81.6464 56.6757 41.2500 47.5000 0.1011 0.1811
AI-ModelScope/Ministral-8B-Instruct-2410 73.7056 66.5971 85.0000 71.2500 0.0997 0.1629
AI-ModelScope/Mistral-7B-v0.1 74.3966 51.7199 12.5000 15.0000 0.1456 0.1329
AI-ModelScope/TinyLlama-1.1B-Chat-v0.4 58.0479 102.3987 22.5000 22.5000 0.0747 0.1156
allenai/OLMoE-1B-7B-0924-Instruct 66.9544 59.7696 37.5000 42.5000 0.2127 0.2610
BAAI/Finance-llama3_1_8B_instruct 95.4692 65.3383 58.7500 57.5000 0.0812 0.1262
BAAI/Hospitality-llama3_1_8B_instruct 91.7153 62.6340 61.2500 56.2500 0.0650 0.1210
BAAI/Technology-llama3_1_8B_instruct 80.6653 60.4259 32.5000 36.2500 0.0844 0.1147
ByteDance-Seed/Seed-OSS-36B-Instruct 38.2767 17.4623 86.7500 88.5000 0.1400 0.3135
codefuse-ai/TestGPT-7B 68.6996 49.0781 15.0000 15.0000 0.0756 0.1193
CohereLabs/aya-expanse-8B 88.7216 78.2155 86.7500 86.7500 0.0687 3.8936
Cylingo/Xinyuan-LLM-14B-0428 71.7868 49.5901 86.7500 89.2500 0.0860 0.2501
deepseek-ai/deepseek-llm-7b-base 141.4714 93.0921 20.0000 22.5000 0.1231 0.1760
deepseek-ai/deepseek-llm-7b-chat 124.9381 99.4562 85.0000 81.2500 0.0581 0.5611
deepseek-ai/deepseek-moe-16b-chat 68.0789 60.7028 85.0000 68.7500 0.2346 0.2880
Fengshenbang/Ziya-LLaMA-13B-v1 56.6471 39.3946 61.2500 58.7500 0.0616 0.1163
FlagAlpha/Llama3-Chinese-8B-Instruct 100.3664 70.7829 38.7500 30.0000 0.1091 0.1442
HuggingFaceH4/zephyr-7b-beta 97.4954 51.7445 66.2500 47.5000 0.0802 0.1135
iic/WritingBench-Critic-Model-Qwen-7B 125.5657 96.5148 87.5000 87.5000 0.0593 0.1159
InfiniAI/Megrez-3b-Instruct 142.4497 157.9848 85.0000 85.0000 0.0815 0.0946
JunHowie/Qwen3-0.6B-GPTQ-Int4 108.2950 67.6596 58.7500 21.2500 0.0711 0.1206
JunHowie/Qwen3-1.7B-GPTQ-Int8 124.1477 131.5458 71.2500 38.7500 0.0900 0.1848
JunHowie/Qwen3-8B-GPTQ-Int4 82.8148 109.8259 86.7500 52.5000 0.0800 0.1575
Kedreamix/Xinjing-LM 137.3682 150.4469 80.0000 66.2500 0.0710 0.1214
LLM-Research/gemma-2-9b-it 47.0337 47.1786 85.0000 66.2500 0.1125 0.2271
LLM-Research/gemma-3-1b-it 39.6315 43.8421 47.5000 71.2500 0.2256 0.2829
LLM-Research/gemma-3-1b-it 38.3524 33.8285 47.5000 36.2500 0.2080 0.1673
LLM-Research/Llama-3.2-3B 137.6931 145.1816 15.0000 15.0000 0.0891 0.1399
LLM-Research/Llama-3.2-3B-Instruct 107.1550 95.4333 63.7500 68.7500 0.0533 0.1868
LLM-Research/Llama-Guard-3-8B 74.5048 73.5737 33.7500 22.5000 0.0861 0.1248
LLM-Research/Llama3-8B-Chinese-Chat 69.0446 66.6263 85.0000 85.0000 0.0823 0.3008
LLM-Research/Meta-Llama-3-8B-Instruct 167.5121 27.8093 85.0000 92.7500 0.0778 0.2426
LLM-Research/Meta-Llama-3-8B-Instruct-GPTQ 199.0842 175.9663 57.5000 71.2500 0.1028 0.1520
LLM-Research/Meta-Llama-3.1-70B-Instruct-AWQ-INT4 34.9493 18.1700 87.5000 85.0000 0.1327 0.2035
LLM-Research/Meta-Llama-3.1-8B-Instruct-AWQ-INT4 93.1869 77.1093 85.0000 85.0000 0.0665 0.1753
LLM-Research/OpenHermes-2.5-Mistral-7B 78.2992 51.0257 75.0000 75.0000 0.0797 0.1161
LLM-Research/Phi-3-mini-4k-instruct 65.0090 59.8164 45.0000 40.0000 0.0632 0.1004
LLM-Research/Qwen2-7B 170.2887 126.6331 77.5000 78.2500 0.0787 0.1345
LLM-Research/Starling-LM-7B-beta 73.7987 49.5925 66.2500 71.2500 0.0952 0.5098
LLM-Research/tulu-2-dpo-7b 60.8343 47.6062 70.0000 72.5000 0.0618 0.0997
m-a-p/neo_7b_instruct_v0.1 178.2949 137.2681 71.2500 72.5000 0.0839 0.1358
mistralai/Devstral-Small-2507 56.7985 42.3061 88.7500 91.0000 0.0698 0.1193
mistralai/Mistral-Small-24B-Instruct-2501 57.3654 42.7280 86.7500 87.5000 0.0899 0.1340
mlabonne/EvolCodeLlama-7b 53.7677 43.3601 5.0000 5.0000 0.1003 0.1287
modelscope/zephyr-7b-beta 81.4112 52.4249 65.0000 47.5000 0.0835 0.2036
neuralmagic/Meta-Llama-3.1-8B-quantized.w8a8 157.2308 130.4350 10.0000 10.0000 0.0638 0.2007
neuralmagic/Qwen2-1.5B-Instruct-quantized.w8a8 133.1439 136.2916 80.0000 80.0000 0.0564 0.0941
neuralmagic/SmolLM-1.7B-Instruct-quantized.w8a8 105.3004 107.6412 10.0000 10.0000 0.0886 0.0876
nv-community/Minitron-4B-Base 63.8192 69.2841 5.0000 5.0000 0.0706 0.0917
openai-mirror/gpt-oss-safeguard-20b 112.4384 86.9659 61.2500 72.0000 0.2067 0.4129
OpenBMB/MiniCPM-1B-sft-bf16 61.4045 71.6924 66.2500 75.0000 0.0748 0.1010
OpenBMB/MiniCPM-2B-dpo-fp16 61.8623 82.9386 80.0000 71.2500 0.1056 0.1071
OpenBMB/MiniCPM-2B-sft-fp32 74.4678 89.2962 65.0000 55.0000 0.0996 0.1408
OpenBMB/MiniCPM3-4B 28.2210 21.3110 86.7500 86.7500 0.1020 0.1905
OpenBMB/MiniCPM4-0.5B 82.2793 93.0776 23.7500 15.0000 0.0606 0.1143
OpenBMB/MiniCPM4-8B 60.5837 57.0162 87.5000 52.5000 0.0921 0.1482
OpenBMB/MiniCPM4-8B-marlin-vLLM 57.5381 58.2351 85.0000 72.0000 0.1033 0.1107
OpenBMB/MiniCPM4.1-8B 61.4557 51.5120 89.2500 86.7500 0.0784 0.1290
PaddlePaddle/ERNIE-4.5-0.3B-PT 144.5465 185.2054 52.5000 47.5000 0.0837 0.0902
prithivMLmods/Llama-Sentient-3.2-3B-Instruct 147.0239 168.6519 40.0000 40.0000 0.0661 0.1230
prithivMLmods/Qwen-UMLS-7B-Instruct 122.8389 89.8736 55.0000 55.0000 0.0584 0.1061
QuantTrio/Qwen3-30B-A3B-Instruct-2507-GPTQ-Int8 40.1016 22.6581 91.7500 68.0000 0.0915 0.2704
Qwen/Qwen-1_8B-Chat-Int4 536.3839 192.9054 28.7500 25.0000 0.0517 0.0936
Qwen/Qwen-1_8B-Chat-Int8 425.9918 95.9929 42.5000 85.0000 0.0549 0.1754
Qwen/Qwen-14B 64.3123 157.3503 38.7500 33.7500 0.0912 0.0858
Qwen/Qwen-14B-Chat-Int4 84.9682 148.9078 68.7500 85.0000 0.0971 0.1298
Qwen/Qwen-14B-Chat-Int8 103.0940 56.3855 85.0000 21.2500 0.0758 0.1443 该模型在沐曦卡上生成质量要差于A100
Qwen/Qwen-72B-Chat-Int4 55.1679 260.1285 85.0000 47.5000 0.1360 0.1411
Qwen/Qwen-72B-Chat-Int8 45.9768 83.0130 68.0000 58.7500 0.1172 0.1511
Qwen/Qwen-7B-Chat-Int4 119.8944 102.6521 55.0000 55.0000 0.0831 0.1092
Qwen/Qwen-7B-Chat-Int4 117.8753 89.0941 55.0000 37.5000 0.0761 0.1086
Qwen/Qwen-7B-Chat-Int8 128.7233 107.4733 40.0000 80.0000 0.0545 0.1578
Qwen/Qwen1.5-0.5B-Chat-GPTQ-Int8 168.5100 135.2830 33.7500 33.7500 0.0530 0.0869
Qwen/Qwen1.5-1.8B-Chat-GPTQ-Int4 153.0596 132.3559 33.7500 63.7500 0.0557 0.1316
Qwen/Qwen1.5-14B-Chat-AWQ 98.3736 74.0728 91.5000 88.5000 0.0725 0.1188
Qwen/Qwen1.5-14B-Chat-GPTQ-Int4 77.7489 92.8893 88.5000 88.5000 0.0863 0.1030
Qwen/Qwen1.5-14B-Chat-GPTQ-Int8 90.9851 79.5202 88.5000 90.2500 0.0716 0.1136
Qwen/Qwen1.5-32B-Chat-GPTQ-Int4 58.2218 51.3081 92.2500 91.0000 0.0775 0.1392
Qwen/Qwen1.5-72B-Chat-GPTQ-Int4 47.0482 28.5930 92.7500 92.7500 0.1314 0.3305
Qwen/Qwen1.5-7B-Chat-GPTQ-Int4 111.7481 110.7277 88.0000 86.7500 0.0857 0.0978
Qwen/Qwen2-72B-Instruct-GPTQ-Int4 48.2245 29.6541 92.7500 92.7500 0.1091 0.2308
Qwen/Qwen2-7B-Instruct-GPTQ-Int4 129.1925 127.4951 88.5000 88.5000 0.0632 0.1595
Qwen/Qwen2-7B-Instruct-GPTQ-Int8 120.7039 120.5521 89.2500 91.0000 0.0589 0.0928
Qwen/Qwen2.5-0.5B 190.6378 143.7020 12.5000 80.0000 0.0569 0.0966
Qwen/Qwen2.5-0.5B-Instruct 157.0171 74.5845 66.2500 90.0000 0.0524 0.1228
Qwen/Qwen2.5-1.5B-Instruct 132.3709 108.0231 85.0000 85.0000 0.0784 0.1907
Qwen/Qwen2.5-1.5B-Instruct-GPTQ-Int4 99.1006 111.6715 80.0000 85.0000 0.0832 0.0998
Qwen/Qwen2.5-14B-Instruct-1M 73.2996 50.5570 92.7500 91.0000 0.0736 0.1316
Qwen/Qwen2.5-14B-Instruct-GPTQ-Int4 79.5701 72.2741 91.0000 91.0000 0.0738 0.1219
Qwen/Qwen2.5-14B-Instruct-GPTQ-Int8 81.3902 70.3944 91.0000 91.0000 0.0588 0.3164
Qwen/Qwen2.5-32B-Instruct-GPTQ-Int4 60.0678 54.5765 90.5000 91.0000 0.1023 0.1855
Qwen/Qwen2.5-3B 102.8492 124.4283 47.5000 50.0000 0.0830 0.1048
Qwen/Qwen2.5-72B-Instruct-GPTQ-Int4 46.5678 29.5256 91.0000 70.5000 0.1013 0.2163
Qwen/Qwen2.5-7B-Instruct-1M 97.2979 92.4331 89.2500 89.2500 0.0685 0.1017
Qwen/Qwen2.5-7B-Instruct-AWQ 115.5071 113.5233 88.5000 91.0000 0.0599 0.0982
Qwen/Qwen2.5-7B-Instruct-GPTQ-Int4 118.1169 133.1432 87.5000 87.5000 0.0603 0.1551
Qwen/Qwen2.5-Coder-14B-Instruct-AWQ 47.8161 52.9300 87.5000 87.5000 0.0854 0.1162
Qwen/Qwen2.5-Coder-14B-Instruct-GPTQ-Int4 70.0316 68.4585 87.5000 73.7500 0.0694 0.1246
Qwen/Qwen2.5-Coder-32B-Instruct-GPTQ-Int4 60.2992 55.2420 91.0000 91.0000 0.1108 0.2650
Qwen/Qwen2.5-Coder-7B 135.1152 115.0369 46.7500 63.7500 0.0979 0.2146
Qwen/Qwen2.5-Coder-7B-Instruct-GPTQ-Int8 108.4975 100.5769 87.5000 87.5000 0.0646 0.1794
Qwen/Qwen3-0.6B 115.7984 128.5600 56.2500 72.5000 0.0890 0.1073
Qwen/Qwen3-0.6B-GPTQ-Int8 117.4333 95.0022 75.0000 33.7500 0.0891 0.1146
Qwen/Qwen3-1___7B 123.6276 55.1110 81.7500 86.7500 0.0931 0.2069
Qwen/Qwen3-30B-A3B-Base 36.5579 145.1734 86.0000 65.0000 0.1890 0.0983
Qwen/Qwen3-30B-A3B-GPTQ-Int4 41.5809 95.4118 88.5000 66.2500 0.0818 0.1298
Qwen/Qwen3-32B-GPTQ-Int8 53.9982 41.3361 86.7500 86.7500 0.1501 0.2713
Qwen/Qwen3-4B 167.1038 83.0732 87.5000 66.2500 0.0587 0.1159
Qwen/Qwen3-4B 171.1984 105.4759 89.2500 84.2500 0.0598 0.1105
Qwen/Qwen3-4B-AWQ 76.4882 91.4280 86.7500 88.5000 0.0922 0.1245
Qwen/Qwen3-4B-Instruct-2507 65.4432 71.7888 91.7500 91.7500 0.0966 0.1285
Qwen/Qwen3-4B-SafeRL 78.8314 96.6840 87.5000 88.5000 0.0930 0.1174
Qwen/Qwen3-4B-Thinking-2507 73.3587 52.6143 81.7500 88.5000 0.0799 0.2663
Qwen/Qwen3-8B-AWQ 94.2630 67.3837 88.5000 86.7500 0.0990 0.1425
QwenCollection/Hercules-Mini-1.8B 202.5339 202.1224 28.7500 28.7500 0.0517 0.0855
QwenCollection/Ragas-critic-llm-Qwen1.5-GPTQ 170.6923 136.0126 35.0000 25.0000 0.0667 0.1142
RUC-DataLab/DeepAnalyze-8B 84.5026 84.9213 86.7500 83.5000 0.1118 0.1673
shakechen/Llama-2-7b-chat-hf 260.9870 34.1061 61.2500 91.0000 0.0892 0.1960
Shanghai_AI_Laboratory/internlm-20b 54.0570 40.9779 49.2500 71.2500 0.1376 0.2653
Shanghai_AI_Laboratory/internlm-chat-20b 59.3568 44.0583 85.0000 85.0000 0.0789 0.1403
Shanghai_AI_Laboratory/internlm2-chat-1_8b 137.9855 150.8975 22.5000 31.2500 0.0874 0.1612
tclf90/Codestral-22B-v0.1-hf-GPTQ-Int4 69.1961 71.7657 80.0000 70.0000 0.1810 0.2461
tclf90/deepseek-r1-distill-qwen-14b-gptq-int4 61.5092 59.0025 85.0000 85.0000 0.0786 0.1791
tclf90/deepseek-r1-distill-qwen-32b-gptq-int4 63.7344 54.3297 88.0000 86.7500 0.1675 0.2525
tclf90/deepseek-r1-distill-qwen-32b-gptq-int8 59.9314 45.7905 86.7500 86.7500 0.1491 0.2839
tclf90/deepseek-r1-distill-qwen-7b-gptq-int4 134.7569 141.3986 80.0000 85.0000 0.0892 0.2778
tclf90/glm-4-9b-chat-GPTQ-Int4 92.2061 97.6775 89.2500 91.7500 0.0735 0.4389
tclf90/glm-4-9b-chat-GPTQ-Int8 67.4918 93.5178 90.5000 86.7500 0.1037 0.1350
tclf90/Qwen2-14B-merge-GPTQ-Int8 68.0706 73.0019 88.5000 88.5000 0.0741 0.1217
tclf90/qwen2.5-14b-instruct-1m-gptq-int4 80.4909 71.7343 91.0000 91.0000 0.0720 0.1329
tclf90/qwen2.5-72b-instruct-gptq-int4 38.6166 34.9558 91.7500 52.5000 0.1053 0.5529
tclf90/Qwen3-32B-GPTQ-Int4 54.3526 38.4391 86.7500 88.5000 0.1470 0.2276
tclf90/Qwen3-32B-GPTQ-Int4 60.6483 42.8220 86.7500 86.7500 0.1651 0.2262
tclf90/Qwen3-32B-GPTQ-Int8 48.2039 148.4290 86.7500 70.0000 0.1526 0.0950
tclf90/qwq-32b-gptq-int4 60.3297 53.4619 87.5000 86.7500 0.1581 0.4379
tclf90/qwq-32b-gptq-int8 52.0826 41.4700 86.7500 87.5000 0.1853 0.2502
TheBloke/Kimiko-7B-fp16 52.3951 41.4855 15.0000 15.0000 0.0947 0.1223
tiiuae/falcon-7b-instruct 177.4328 147.2327 20.0000 20.0000 0.0906 0.1180
TongyiFinance/Tongyi-Finance-14B-Chat 161.2871 55.1869 52.5000 63.7500 0.0970 0.2396
TongyiFinance/Tongyi-Finance-14B-Chat-Int4 144.2085 114.2191 57.5000 38.7500 0.0592 0.1210
TongyiFinance/Tongyi-Finance-14B-Chat-Int4 147.6310 129.5033 57.5000 57.5000 0.0694 0.1123
UnicomAI/Unichat-llama3.2-Chinese-1B 170.9294 181.6792 26.2500 25.0000 0.0594 0.1311
unsloth/Phi-3.5-mini-instruct 39.4028 38.0348 80.0000 77.5000 0.0716 0.1253
XGenerationLab/XiYanSQL-QwenCoder-3B-2502 111.9181 105.4054 80.0000 85.0000 0.0593 0.1060
Xunzillm4cc/Xunzi-Qwen1.5-4B 99.2706 102.2685 22.5000 25.0000 0.0811 0.0982
Xunzillm4cc/Xunzi-Qwen2-1.5B 125.9543 137.9787 20.0000 17.5000 0.0588 0.0903
ZhipuAI/chatglm3-6b-base 129.0337 40.0233 38.7500 71.2500 0.1349 0.2365
ZhipuAI/glm-4-9b-chat-1m 102.4445 77.4381 89.7500 88.7500 0.0911 0.1357
ZhipuAI/glm-4-9b-chat-hf 109.1148 71.8195 85.0000 85.0000 0.0900 0.1838
ZhipuAI/GLM-Z1-32B-0414 55.9116 41.5245 88.5000 88.5000 0.1048 0.2995
ZhipuAI/GLM-Z1-9B-0414 90.9342 71.1734 85.0000 86.7500 0.0879 0.9642
ZhipuAI/LongWriter-glm4-9b 100.4160 81.4277 86.7500 86.7500 0.1221 0.1758
zpeng1989/TCM_DeepSeek_LLM 98.9219 64.9526 82.5000 80.0000 0.0721 0.1533