Xiaomi
availableShows if the model has enough results for an index.MiMo-V2.5
MiMo-V2.5 is a reasoning model from Xiaomi. 13 benchmarks count toward its score, in 5 categories.
IndexOverall score out of 100.55.7 ±7.0
CoverageShare of the index weight with results.75%
SpeedOutput tokens per second.34/s
Input / 1MUS dollars per 1M input tokens.$0.14
Output / 1MUS dollars per 1M output tokens.$0.28
ContextMaximum tokens in one request.1.05M
EloLMArena rating and rank.1427 (#90)
The index is a score out of 100. The ± range shows how much it can change.
44,466 votes. Elo shows what people prefer. It does not change the score.
CapabilitiesScore per category, out of 100.
Out of 100Results
13 counted| BenchmarkThe test name. | CategoryThe capability that the test measures. | ResultThe score from the publisher. | IndexThis result as a score out of 100. | RunThe settings of the run. | DateDate of the result. | Published byThe source of the result. |
|---|---|---|---|---|---|---|
| Video-MME with subtitle | Multimodal | 87.7% | — | — | — | Qwen |
| MMLU Pro | Knowledge | 82.9% | 51.2 | — | 1 Sept 2026 | Vals AI |
| GPQA Diamond | Knowledge | 81.6% | 53.5 | — | 1 Sept 2026 | Vals AI |
| LiveCodeBench | Coding | 81.5% | 58.4 | — | 1 Sept 2026 | Vals AI |
| CharXiv Reasoning | Multimodal | 81.0% | 58.3 | — | — | CharXiv authors |
| MMMU Pro | Multimodal | 80.0% | 57.5 | — | 1 Sept 2026 | Vals AI |
| Massive Multi-discipline Multimodal Understanding Pro | Multimodal | 77.9% | 54.1 | — | — | MMMU-Pro authors |
| SWE-bench | Coding | 71.0% | 54.5 | — | 1 Sept 2026 | Vals AI |
| Claw-Eval | Agentic | 62.3% | 56.3 | — | — | Bowen Ye et al. |
| Terminal-Bench 2.1 | Agentic | 60.7% | 59.9 | — | 21 Sept 2026 | Vals AI |
| SWE-bench Pro | Coding | 56.1% | 58.3 | — | — | Xiang Deng et al. |
| Gert Labs Composite Game Benchmark | Agentic | 46.9% | 54.1 | — | — | Gert Labs |
| Vibe Code Bench v1.1 | Coding | 42.2% | 59.7 | OpenHands | 21 Sept 2026 | Vals AI |
| MM-ClawBench | Agentic | 23.8% | — | — | — | MiniMax |
| ResearchClawBench | Agentic | 16.9% | — | — | — | InternScience |
| ProofBench v1.1 | Math | 16.0% | 55.9 | — | 21 Sept 2026 | Vals AI |
| Code Migration | Coding | 14.2% | 54.0 | — | 21 Sept 2026 | Vals AI |
13 benchmarks count, from 14 of 17 results. A grey row does not count. Too few models took that benchmark.