# gpt-oss-120b vs MiniMax-M2.5

> MiniMax-M2.5 is the stronger model overall, scoring 38.3 to 36.3 on the Noometry Index. gpt-oss-120b costs 7.5× less per token, which makes it the better buy when MiniMax-M2.5's lead doesn't matter for your workload.

- Canonical page: https://noometry.com/compare/gpt-oss-120b-vs-minimax-m2-5
- Last updated: 2026-10-10
- Shared benchmarks: 25

## Summary

- They share 25 benchmarks with published results for both. gpt-oss-120b scores higher in 4 categories and MiniMax-M2.5 in 5 categories; 8 gaps are clear of the uncertainty.
- The widest gap is in math, where gpt-oss-120b leads 52.5 to 26.9.
- The biggest single-benchmark swing is SWE-bench Verified (bash only): 26% for gpt-oss-120b and 75.8% for MiniMax-M2.5.
- gpt-oss-120b is cheaper at $0.037 / $0.17 per million input/output tokens, against $0.30 / $1.20 for MiniMax-M2.5.
- MiniMax-M2.5 accepts more context: 205K tokens versus 131K.

## Snapshot

| | gpt-oss-120b | MiniMax-M2.5 |
|---|---|---|
| Provider | OpenAI | MiniMax |
| Noometry Index | 36.3 | 38.3 |
| Rank | 217 | 188 |
| Context | 131K | 205K |
| Input $/M | $0.037 | $0.30 |
| Output $/M | $0.17 | $1.20 |
| Weights | Open | Open |

## Coding

- gpt-oss-120b: 33.5 (#256)
- MiniMax-M2.5: 48.1 (#58)

| Benchmark | gpt-oss-120b | MiniMax-M2.5 |
|---|---|---|
| SWE-bench Verified (bash only) | 26% | 75.8% |
| LMArena Coding | 1380 | 1381 |
| ALE-Bench | 575.62 | 618.17 |
| Aider Polyglot | 41.8% | — |
| LMArena WebDev | — | 1387 |
| SWE-bench Multilingual | — | 68.3% |
| SciCode | 36% | — |
| WeirdML | 48.2% | — |
| AlgoTune | 1.41 | — |

## Agentic & Tool Use

- gpt-oss-120b: 12.2 (#153)
- MiniMax-M2.5: 30.4 (#77)

| Benchmark | gpt-oss-120b | MiniMax-M2.5 |
|---|---|---|
| Terminal-Bench | 18.7% | 42.7% |
| Vending-Bench 2 | -21.53 | -23.16 |
| APEX-Agents | 4.4% | — |
| METR Time Horizons | 56.6% | — |

## Reasoning

- gpt-oss-120b: 20.0 (#245)
- MiniMax-M2.5: 17.5 (#292)

| Benchmark | gpt-oss-120b | MiniMax-M2.5 |
|---|---|---|
| Kagi LLM Benchmark | 58.6% | 55.2% |
| LMArena Hard Prompts | 1364 | 1372 |
| Epoch Capabilities Index | 139.93 | 146.68 |
| ARC-AGI-2 | — | 4.9% |
| SimpleBench | 22.1% | — |
| NYT Connections (extended) | — | 16.8% |
| ARC-AGI-1 | — | 63.7% |
| CritPt | 1.1% | — |
| Chess Puzzles | 20% | — |
| Mystery Game Puzzles | 2% | — |
| DTBench | 76.3% | — |
| LMCA | 22.1% | — |
| Surface Evolver Bench | 25% | — |

## Math

- gpt-oss-120b: 52.5 (#50)
- MiniMax-M2.5: 26.9 (#253)

| Benchmark | gpt-oss-120b | MiniMax-M2.5 |
|---|---|---|
| LMArena Math | 1389 | 1378 |
| OTIS Mock AIME 2024-2025 | 88.9% | — |
| ProofBench | — | 4% |
| Omni-MATH | 68.8% | — |

## Knowledge

- gpt-oss-120b: 42.4 (#96)
- MiniMax-M2.5: 39.2 (#135)

| Benchmark | gpt-oss-120b | MiniMax-M2.5 |
|---|---|---|
| Vectara Hallucination Rate | 14.2% | 9.1% |
| LMArena Expert | 1356 | 1379 |
| GPQA Diamond | 75.8% | — |
| MMLU-Pro | 79.5% | — |
| Confabulations | 15.7% | — |
| GPQA (HELM) | 68.4% | — |

## Multilingual

- gpt-oss-120b: 48.0 (#147)
- MiniMax-M2.5: 47.1 (#152)

| Benchmark | gpt-oss-120b | MiniMax-M2.5 |
|---|---|---|
| LMArena Non-English | 1351 | 1338 |
| LMArena Chinese | 1385 | 1393 |
| LMArena French | 1369 | 1362 |
| LMArena German | 1353 | 1362 |
| LMArena Japanese | 1331 | 1171 |
| LMArena Korean | 1282 | 1232 |
| LMArena Russian | 1343 | 1358 |
| LMArena Spanish | 1389 | 1354 |

## Instruction Following

- gpt-oss-120b: 69.3 (#173)
- MiniMax-M2.5: 71.5 (#148)

| Benchmark | gpt-oss-120b | MiniMax-M2.5 |
|---|---|---|
| LMArena Instruction Following | 1318 | 1353 |
| IFEval | 83.6% | — |

## Long Context

- gpt-oss-120b: 31.4 (#278)
- MiniMax-M2.5: 37.5 (#216)

| Benchmark | gpt-oss-120b | MiniMax-M2.5 |
|---|---|---|
| LMArena Longer Query | 1319 | 1366 |
| Fiction.LiveBench | 44.4% | — |
| CL-bench | — | 11.4% |
| CL-bench Life | — | 6.3% |

## Writing & Preference

- gpt-oss-120b: 46.5 (#217)
- MiniMax-M2.5: 53.9 (#153)

| Benchmark | gpt-oss-120b | MiniMax-M2.5 |
|---|---|---|
| LMArena Text | 1365 | 1359 |
| LMArena Creative Writing | 1275 | 1331 |
| EQ-Bench Creative Writing | 961 | 1361 |
| LMArena Multi-Turn | 1340 | 1364 |
| Short-Story Creative Writing | 77.1% | — |
| WildBench | 84.5% | — |

## FAQ

### Is gpt-oss-120b better than MiniMax-M2.5?

MiniMax-M2.5 is the stronger model overall, scoring 38.3 to 36.3 on the Noometry Index. gpt-oss-120b costs 7.5× less per token, which makes it the better buy when MiniMax-M2.5's lead doesn't matter for your workload.

### Which is cheaper, gpt-oss-120b or MiniMax-M2.5?

gpt-oss-120b is cheaper. It lists at $0.037 per million input tokens and $0.17 per million output tokens; MiniMax-M2.5 lists at $0.30 and $1.20.

### Is gpt-oss-120b or MiniMax-M2.5 better for coding?

MiniMax-M2.5 scores higher on coding benchmarks: 48.1 versus 33.5 in the Noometry coding category.

### Which has the bigger context window?

MiniMax-M2.5 does, with 205K tokens against 131K.

### How many benchmarks do gpt-oss-120b and MiniMax-M2.5 share?

25 benchmarks have published results for both models. gpt-oss-120b has 48 scored results on Noometry and MiniMax-M2.5 has 33.