DeepSeek-V3 的综合能力
DeepSeek-V3 在推理速度上相较历史模型有了大幅提升。
在目前大模型主流榜单中，DeepSeek-V3 在开源模型中位列榜首，与世界上最先进的闭源模型不分伯仲。
| Benchmark (Metric) | DeepSeek V3 | DeepSeek V2.5 | Qwen2.5 | Llama3.1 | Claude-3.5 | GPT-4o | |
|---|---|---|---|---|---|---|---|
| 0905 | 72B-Inst | 405B-Inst | Sonnet-1022 | 0513 | |||
| Architecture | MoE | MoE | Dense | Dense | – | – | |
| # Activated Params | 37B | 21B | 72B | 405B | – | – | |
| # Total Params | 671B | 236B | 72B | 405B | – | – | |
| English | MMLU (EM) | 88.5 | 80.6 | 85.3 | 88.6 | 88.3 | 87.2 |
| MMLU-Redux (EM) | 89.1 | 80.3 | 85.6 | 86.2 | 88.9 | 88.0 | |
| MMLU-Pro (EM) | 75.9 | 66.2 | 71.6 | 73.3 | 78.0 | 72.6 | |
| DROP (3-shot F1) | 91.6 | 87.8 | 76.7 | 88.7 | 88.3 | 83.7 | |
| IF-Eval (Prompt Strict) | 86.1 | 80.6 | 84.1 | 86.0 | 86.5 | 84.3 | |
| GPQA-Diamond (Pass@1) | 59.1 | 41.3 | 49.0 | 51.1 | 65.0 | 49.9 | |
| SimpleQA (Correct) | 24.9 | 10.2 | 9.1 | 17.1 | 28.4 | 38.2 | |
| FRAMES (Acc.) | 73.3 | 65.4 | 69.8 | 70.0 | 72.5 | 80.5 | |
| LongBench v2 (Acc.) | 48.7 | 35.4 | 39.4 | 36.1 | 41.0 | 48.1 | |
| Code | HumanEval-Mul (Pass@1) | 82.6 | 77.4 | 77.3 | 77.2 | 81.7 | 80.5 |
| LiveCodeBench (Pass@1-COT) | 40.5 | 29.2 | 31.1 | 28.4 | 36.3 | 33.4 | |
| LiveCodeBench (Pass@1) | 37.6 | 28.4 | 28.7 | 30.1 | 32.8 | 34.2 | |
| Codeforces (Percentile) | 51.6 | 35.6 | 24.8 | 25.3 | 20.3 | 23.6 | |
| SWE Verified (Resolved) | 42.0 | 22.6 | 23.8 | 24.5 | 50.8 | 38.8 | |
| Aider-Edit (Acc.) | 79.7 | 71.6 | 65.4 | 63.9 | 84.2 | 72.9 | |
| Aider-Polyglot (Acc.) | 49.6 | 18.2 | 7.6 | 5.8 | 45.3 | 16.0 | |
| Math | AIME 2024 (Pass@1) | 39.2 | 16.7 | 23.3 | 23.3 | 16.0 | 9.3 |
| MATH-500 (EM) | 90.2 | 74.7 | 80.0 | 73.8 | 78.3 | 74.6 | |
| CNMO 2024 (Pass@1) | 43.2 | 10.8 | 15.9 | 6.8 | 13.1 | 10.8 | |
| Chinese | CLUEWSC (EM) | 90.9 | 90.4 | 91.4 | 84.7 | 85.4 | 87.9 |
| C-Eval (EM) | 86.5 | 79.5 | 86.1 | 61.5 | 76.7 | 76.0 | |
| C-SimpleQA (Correct) | 64.1 | 54.1 | 48.4 | 50.4 | 51.3 | 59.3 |