# gpt-oss-120b vs MiMo-V2.5

> MiMo-V2.5 is the stronger model overall, scoring 43.0 to 36.0 on the Noometry Index. gpt-oss-120b costs 2.5× less per token, which makes it the better buy when MiMo-V2.5's lead doesn't matter for your workload.

- Canonical page: https://noometry.com/compare/gpt-oss-120b-vs-mimo-v2-5
- Last updated: 2026-10-10
- Shared benchmarks: 20

## Summary

- They share 20 benchmarks with published results for both. gpt-oss-120b scores higher in 2 categories and MiMo-V2.5 in 6 categories; 8 gaps are clear of the uncertainty.
- The widest gap is in math, where gpt-oss-120b leads 50.6 to 35.4.
- The biggest single-benchmark swing is SciCode: 36% for gpt-oss-120b and 43.1% for MiMo-V2.5.
- gpt-oss-120b is cheaper at $0.037 / $0.17 per million input/output tokens, against $0.14 / $0.28 for MiMo-V2.5.
- MiMo-V2.5 accepts more context: 1.05M tokens versus 131K.

## Snapshot

| | gpt-oss-120b | MiMo-V2.5 |
|---|---|---|
| Provider | OpenAI | Xiaomi |
| Noometry Index | 36.0 | 43.0 |
| Rank | 210 | 89 |
| Context | 131K | 1.05M |
| Input $/M | $0.037 | $0.14 |
| Output $/M | $0.17 | $0.28 |
| Weights | Open | Open |

## Coding

- gpt-oss-120b: 33.2 (#251)
- MiMo-V2.5: 43.6 (#75)

| Benchmark | gpt-oss-120b | MiMo-V2.5 |
|---|---|---|
| SciCode | 36% | 43.1% |
| LMArena Coding | 1380 | 1469 |
| ALE-Bench | 575.62 | 513.95 |
| SWE-bench Verified (bash only) | 26% | — |
| Aider Polyglot | 41.8% | — |
| LMArena WebDev | — | 1438 |
| WeirdML | 48.2% | — |
| AlgoTune | 1.41 | — |

## Agentic & Tool Use

- gpt-oss-120b: 12.1 (#145)
- MiMo-V2.5: —

| Benchmark | gpt-oss-120b | MiMo-V2.5 |
|---|---|---|
| Terminal-Bench | 18.7% | — |
| APEX-Agents | 4.4% | — |
| METR Time Horizons | 56.6% | — |
| Vending-Bench 2 | -21.53 | — |

## Reasoning

- gpt-oss-120b: 19.5 (#236)
- MiMo-V2.5: 27.8 (#98)

| Benchmark | gpt-oss-120b | MiMo-V2.5 |
|---|---|---|
| CritPt | 1.1% | 3.7% |
| LMArena Hard Prompts | 1364 | 1450 |
| SimpleBench | 22.1% | — |
| Kagi LLM Benchmark | 58.6% | — |
| Chess Puzzles | 20% | — |
| Mystery Game Puzzles | 2% | — |
| DTBench | 76.3% | — |
| LMCA | 22.1% | — |
| Surface Evolver Bench | 25% | — |
| Epoch Capabilities Index | 139.94 | — |

## Math

- gpt-oss-120b: 50.6 (#43)
- MiMo-V2.5: 35.4 (#145)

| Benchmark | gpt-oss-120b | MiMo-V2.5 |
|---|---|---|
| LMArena Math | 1388 | 1436 |
| OTIS Mock AIME 2024-2025 | 88.9% | — |
| ProofBench | — | 16% |
| Omni-MATH | 68.8% | — |

## Knowledge

- gpt-oss-120b: 42.3 (#89)
- MiMo-V2.5: 40.2 (#109)

| Benchmark | gpt-oss-120b | MiMo-V2.5 |
|---|---|---|
| LMArena Expert | 1356 | 1459 |
| GPQA Diamond | 75.8% | — |
| MMLU-Pro | 79.5% | — |
| Confabulations | 15.7% | — |
| Vectara Hallucination Rate | 14.2% | — |
| GPQA (HELM) | 68.4% | — |

## Multimodal

- gpt-oss-120b: —
- MiMo-V2.5: 39.0 (#53)

| Benchmark | gpt-oss-120b | MiMo-V2.5 |
|---|---|---|
| LMArena Vision | — | 1245 |

## Multilingual

- gpt-oss-120b: 48.2 (#142)
- MiMo-V2.5: 52.0 (#96)

| Benchmark | gpt-oss-120b | MiMo-V2.5 |
|---|---|---|
| LMArena Non-English | 1350 | 1404 |
| LMArena Chinese | 1384 | 1467 |
| LMArena French | 1370 | 1447 |
| LMArena German | 1355 | 1421 |
| LMArena Japanese | 1332 | 1304 |
| LMArena Korean | 1283 | 1363 |
| LMArena Russian | 1343 | 1395 |
| LMArena Spanish | 1388 | 1412 |

## Instruction Following

- gpt-oss-120b: 69.5 (#168)
- MiMo-V2.5: 75.7 (#55)

| Benchmark | gpt-oss-120b | MiMo-V2.5 |
|---|---|---|
| LMArena Instruction Following | 1318 | 1433 |
| IFEval | 83.6% | — |

## Long Context

- gpt-oss-120b: 31.4 (#273)
- MiMo-V2.5: 44.1 (#69)

| Benchmark | gpt-oss-120b | MiMo-V2.5 |
|---|---|---|
| LMArena Longer Query | 1319 | 1444 |
| Fiction.LiveBench | 44.4% | — |

## Writing & Preference

- gpt-oss-120b: 46.7 (#213)
- MiMo-V2.5: 61.8 (#82)

| Benchmark | gpt-oss-120b | MiMo-V2.5 |
|---|---|---|
| LMArena Text | 1366 | 1427 |
| LMArena Creative Writing | 1274 | 1392 |
| LMArena Multi-Turn | 1340 | 1445 |
| Short-Story Creative Writing | 77.1% | — |
| EQ-Bench Creative Writing | 961 | — |
| WildBench | 84.5% | — |

## FAQ

### Is gpt-oss-120b better than MiMo-V2.5?

MiMo-V2.5 is the stronger model overall, scoring 43.0 to 36.0 on the Noometry Index. gpt-oss-120b costs 2.5× less per token, which makes it the better buy when MiMo-V2.5's lead doesn't matter for your workload.

### Which is cheaper, gpt-oss-120b or MiMo-V2.5?

gpt-oss-120b is cheaper. It lists at $0.037 per million input tokens and $0.17 per million output tokens; MiMo-V2.5 lists at $0.14 and $0.28.

### Is gpt-oss-120b or MiMo-V2.5 better for coding?

MiMo-V2.5 scores higher on coding benchmarks: 43.6 versus 33.2 in the Noometry coding category.

### Which has the bigger context window?

MiMo-V2.5 does, with 1.05M tokens against 131K.

### How many benchmarks do gpt-oss-120b and MiMo-V2.5 share?

20 benchmarks have published results for both models. gpt-oss-120b has 48 scored results on Noometry and MiMo-V2.5 has 23.