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A head-to-head benchmark comparison of DeepSeek-R1-Distill-Qwen-14B across 10 evaluations.
We introduce our first-generation reasoning models, DeepSeek-R1-Zero and DeepSeek-R1. DeepSeek-R1-Zero, a model trained via large-scale reinforcement learning (.
Full DeepSeek-R1-Distill-Qwen-14B specs →| Benchmark | DeepSeek-R1-Distill-Qwen-14B |
|---|---|
| code | |
| LiveCodeBench v5 | 53.1% |
| LiveCodeBench v6 | 31.9% |
| general | |
| IFEval | 78.3% |
| MMLU-Pro | 68.8% |
| knowledge | |
| SuperGPQA | 40.6 |
| math | |
| AIME 2024 | 69.7% |
| AIME 2025 | 48.2% |
| MATH-500 | 93.9% |
| reasoning | |
| DROP | 85.5% |
| GPQA Diamond | 59.1% |
Best result per row highlighted in cyan. Each benchmark links to its definition and sources; each model links to its full scorecard.
DeepSeek-R1-Distill-Qwen-14B has the strongest result on LiveCodeBench v5 among the models compared here. See the code-category rows in the table for the full picture.
This comparison covers 10 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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