MiniMax
availableShows if the model has enough results for an index.MiniMax M2.5
MiniMax M2.5 is a non-reasoning model from MiniMax. 10 benchmarks count toward its score, in 5 categories.
IndexOverall score out of 100.50.9 ±7.1
CoverageShare of the index weight with results.80%
SpeedOutput tokens per second.27/s
Input / 1MUS dollars per 1M input tokens.$0.27
Output / 1MUS dollars per 1M output tokens.$1.08
ContextMaximum tokens in one request.205K
EloLMArena rating and rank.1359 (#184)
The index is a score out of 100. The ± range shows how much it can change.
40,843 votes. Elo shows what people prefer. It does not change the score.
CapabilitiesScore per category, out of 100.
Out of 100Results
10 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. |
|---|---|---|---|---|---|---|
| AIME | Math | 88.8% | 55.1 | — | 16 Apr 2026 | Vals AI |
| GPQA Diamond | Knowledge | 82.1% | 54.0 | — | 1 Sept 2026 | Vals AI |
| MMLU Pro | Knowledge | 80.1% | 46.7 | — | 1 Sept 2026 | Vals AI |
| LiveCodeBench | Coding | 79.2% | 56.3 | — | 1 Sept 2026 | Vals AI |
| SWE-bench Verified | Coding | 75.8% | 58.3 | high effort · mini-SWE-agent | 1 Sept 2026 | SWE-bench team |
| SWE-bench | Coding | 74.2% | 57.1 | — | 1 Sept 2026 | Vals AI |
| SWE-bench Multilingual | Multilingual | 68.3% | — | mini-SWE-agent | 20 Feb 2026 | SWE-bench team |
| ARC-AGI-1 (semi-private) | Reasoning | 63.7% | 57.3 | — | — | ARC Prize Foundation |
| Terminal-Bench 2.0 | Agentic | 41.6% | 52.3 | — | 4 Jun 2026 | Vals AI |
| Vibe Code Bench v1.1 | Coding | 14.9% | 48.4 | OpenHands | 21 Sept 2026 | Vals AI |
| IOI v1 | Coding | 6.7% | 43.7 | — | 9 Aug 2026 | Vals AI |
| ARC-AGI-2 (semi-private) | Reasoning | 4.9% | 42.2 | — | — | ARC Prize Foundation |
10 benchmarks count, from 11 of 12 results. A grey row does not count. Too few models took that benchmark.