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A head-to-head benchmark comparison of DeepSeek-R1-Distill-Llama-8B across 15 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-Llama-8B specs →| Benchmark | DeepSeek-R1-Distill-Llama-8B |
|---|---|
| code | |
| HumanEval | 67.54% |
| HumanEval+ | 62.91% |
| LiveCodeBench | 39.6% |
| general | |
| AlpacaEval 2 | 21.85% |
| ArenaHard | 17.17% |
| IFEval | 66.5% |
| MMLU | 45.8% |
| math | |
| AIME 2024 | 80% |
| AIME 2025 | 53.3% |
| GSM8K | 72.18% |
| MATH-500 | 89.1% |
| reasoning | |
| BIG-Bench Hard | 65.71% |
| DROP | 44.46% |
| GPQA Diamond | 49% |
| safety | |
| TruthfulQA | 47.43% |
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-Llama-8B has the strongest result on HumanEval among the models compared here. See the code-category rows in the table for the full picture.
This comparison covers 15 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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