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A head-to-head benchmark comparison of DeepSeek-V3 across 25 evaluations.
We present DeepSeek-V3, a strong Mixture-of-Experts (MoE) language model with 671B total parameters with 37B activated for each token. To achieve efficient infe.
Full DeepSeek-V3 specs →| Benchmark | DeepSeek-V3 |
|---|---|
| code | |
| Aider Polyglot | 49.6% |
| HumanEval | 94.6% |
| HumanEval+ | 91.6% |
| LiveCodeBench | 42.7% |
| LiveCodeBench v5 | 36.2% |
| MBPP+ | 78.8% |
| general | |
| AlpacaEval 2 | 66.5% |
| ArenaHard | 92.1% |
| C-Eval | 86.3% |
| CLUEWSC | 93.5% |
| IFEval | 88% |
| MMLU | 88.5% |
| MMLU-Pro | 76% |
| MMLU-Redux | 88.8% |
| math | |
| AIME 2024 | 39.2% |
| AIME 2025 | 28.8% |
| CNMO 2024 | 33.9% |
| GSM8K | 96.7% |
| MATH | 89.7% |
| MATH-500 | 90.2% |
| reasoning | |
| BIG-Bench Hard | 89.5% |
| DROP | 91.8% |
| GPQA Diamond | 59.1% |
| safety | |
| C-SimpleQA | 68.9% |
| SimpleQA | 24.9% |
Best result per row highlighted in cyan. Each benchmark links to its definition and sources; each model links to its full scorecard.
DeepSeek-V3 has the strongest result on Aider Polyglot among the models compared here. See the code-category rows in the table for the full picture.
This comparison covers 25 benchmarks on which at least one of the selected models has a published score.
Scores are aggregated from official model cards, technical reports and standard public evaluations, and link back to each benchmark's source. They are updated as new results are published.
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