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A head-to-head benchmark comparison of Kimi Linear across 17 evaluations.
We introduce Kimi Linear, a hybrid linear attention architecture that, for the first time, outperforms full attention under fair comparisons across various scen.
Full Kimi Linear specs →| Benchmark | Kimi Linear |
|---|---|
| code | |
| LiveCodeBench v6 | 26% |
| coding | |
| EvalPlus | 61 |
| general | |
| HELMET | 90% |
| LiveBench | 45.2 |
| LongBench v2 | 35% |
| MMLU | 77% |
| MMLU-Pro | 67.4% |
| MMLU-Redux | 80.3% |
| RULER | 84.3% |
| long-context | |
| Frames | 58.8 |
| RepoQA | 68.5 |
| math | |
| AIME 2025 | 21.3% |
| HMMT February 2025 | 12.5% |
| MATH-500 | 81.2% |
| PolyMath-en | 43.6 |
| reasoning | |
| BIG-Bench Hard | 69.4% |
| GPQA Diamond | 62.1% |
Best result per row highlighted in cyan. Each benchmark links to its definition and sources; each model links to its full scorecard.
Kimi Linear has the strongest result on LiveCodeBench v6 among the models compared here. See the code-category rows in the table for the full picture.
This comparison covers 17 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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