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A head-to-head benchmark comparison of MiniMax-M1-40k across 17 evaluations.
We introduce MiniMax-M1, the world's first open-weight, large-scale hybrid-attention reasoning model. MiniMax-M1 is powered by a hybrid Mixture-of-Experts (MoE).
Full MiniMax-M1-40k specs →| Benchmark | MiniMax-M1-40k |
|---|---|
| agentic | |
| TAU-bench Airline | 60% |
| TAU-bench Retail | 67.8% |
| code | |
| FullStackBench | 67.6% |
| LiveCodeBench | 62.3% |
| SWE-bench Verified | 55.6% |
| general | |
| LongBench v2 | 61% |
| MMLU-Pro | 80.6% |
| MultiChallenge | 44.7% |
| OpenAI MRCR (128k) | 76.1% |
| OpenAI MRCR (1M) | 58.6% |
| math | |
| AIME 2024 | 83.3% |
| AIME 2025 | 74.6% |
| MATH-500 | 96% |
| reasoning | |
| GPQA Diamond | 69.2% |
| Humanity's Last Exam | 7.2% |
| ZebraLogic | 80.1% |
| safety | |
| SimpleQA | 17.9% |
Best result per row highlighted in cyan. Each benchmark links to its definition and sources; each model links to its full scorecard.
MiniMax-M1-40k has the strongest result on FullStackBench 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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