# gpt-oss-120b vs Mistral Medium

> gpt-oss-120b and Mistral Medium score almost the same on the Noometry Index (36.3 vs 36.3), so choose on price, context window or the category you care about most.

- Canonical page: https://noometry.com/compare/gpt-oss-120b-vs-mistral-medium
- Last updated: 2026-10-11
- Shared benchmarks: 29

## Summary

- They share 29 benchmarks with published results for both. gpt-oss-120b scores higher in 2 categories and Mistral Medium in 7 categories; 8 gaps are clear of the uncertainty.
- The widest gap is in math, where gpt-oss-120b leads 52.5 to 28.1.
- The biggest single-benchmark swing is OTIS Mock AIME 2024-2025: 88.9% for gpt-oss-120b and 32.2% for Mistral Medium.
- gpt-oss-120b is cheaper at $0.037 / $0.17 per million input/output tokens, against $1.50 / $7.50 for Mistral Medium.
- Mistral Medium accepts more context: 262K tokens versus 131K.

## Snapshot

| | gpt-oss-120b | Mistral Medium |
|---|---|---|
| Provider | OpenAI | Mistral AI |
| Noometry Index | 36.3 | 36.3 |
| Rank | 217 | 218 |
| Context | 131K | 262K |
| Input $/M | $0.037 | $1.50 |
| Output $/M | $0.17 | $7.50 |
| Weights | Open | Open |

## Coding

- gpt-oss-120b: 33.5 (#256)
- Mistral Medium: 34.2 (#243)

| Benchmark | gpt-oss-120b | Mistral Medium |
|---|---|---|
| SciCode | 36% | 40.2% |
| WeirdML | 48.2% | 43.7% |
| LMArena Coding | 1380 | 1434 |
| ALE-Bench | 575.62 | 763.98 |
| FrontierCode | — | 8% |
| SWE-bench Verified (bash only) | 26% | — |
| Aider Polyglot | 41.8% | — |
| AlgoTune | 1.41 | — |

## Agentic & Tool Use

- gpt-oss-120b: 12.2 (#153)
- Mistral Medium: 28.3 (#90)

| Benchmark | gpt-oss-120b | Mistral Medium |
|---|---|---|
| Terminal-Bench | 18.7% | — |
| APEX-Agents | 4.4% | — |
| Berkeley Function Calling Leaderboard | — | 37.7% |
| METR Time Horizons | 56.6% | — |
| Vending-Bench 2 | -21.53 | — |

## Reasoning

- gpt-oss-120b: 20.0 (#245)
- Mistral Medium: 24.0 (#167)

| Benchmark | gpt-oss-120b | Mistral Medium |
|---|---|---|
| Kagi LLM Benchmark | 58.6% | 50% |
| CritPt | 1.1% | 0% |
| LMArena Hard Prompts | 1364 | 1426 |
| DTBench | 76.3% | 75.5% |
| LMCA | 22.1% | 26.1% |
| Surface Evolver Bench | 25% | 26.9% |
| SimpleBench | 22.1% | — |
| Chess Puzzles | 20% | — |
| Mystery Game Puzzles | 2% | — |
| Epoch Capabilities Index | 139.93 | — |

## Math

- gpt-oss-120b: 52.5 (#50)
- Mistral Medium: 28.1 (#245)

| Benchmark | gpt-oss-120b | Mistral Medium |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 88.9% | 32.2% |
| LMArena Math | 1389 | 1408 |
| ProofBench | — | 9% |
| Omni-MATH | 68.8% | — |
| MATH Level 5 | — | 81.6% |
| FrontierMath (Feb 2025 set) | — | 0.3% |

## Knowledge

- gpt-oss-120b: 42.4 (#96)
- Mistral Medium: 25.0 (#265)

| Benchmark | gpt-oss-120b | Mistral Medium |
|---|---|---|
| GPQA Diamond | 75.8% | 59.5% |
| Vectara Hallucination Rate | 14.2% | 22.7% |
| LMArena Expert | 1356 | 1408 |
| Humanity's Last Exam | — | 4.5% |
| MMLU-Pro | 79.5% | — |
| Confabulations | 15.7% | — |
| GPQA (HELM) | 68.4% | — |

## Multimodal

- gpt-oss-120b: —
- Mistral Medium: 35.3 (#88)

| Benchmark | gpt-oss-120b | Mistral Medium |
|---|---|---|
| LMArena Vision | — | 1172 |

## Multilingual

- gpt-oss-120b: 48.0 (#147)
- Mistral Medium: 52.1 (#91)

| Benchmark | gpt-oss-120b | Mistral Medium |
|---|---|---|
| LMArena Non-English | 1351 | 1408 |
| LMArena Chinese | 1385 | 1447 |
| LMArena French | 1369 | 1459 |
| LMArena German | 1353 | 1432 |
| LMArena Japanese | 1331 | 1378 |
| LMArena Korean | 1282 | 1380 |
| LMArena Russian | 1343 | 1411 |
| LMArena Spanish | 1389 | 1433 |

## Instruction Following

- gpt-oss-120b: 69.3 (#173)
- Mistral Medium: 73.7 (#116)

| Benchmark | gpt-oss-120b | Mistral Medium |
|---|---|---|
| LMArena Instruction Following | 1318 | 1398 |
| IFEval | 83.6% | — |

## Long Context

- gpt-oss-120b: 31.4 (#278)
- Mistral Medium: 42.9 (#114)

| Benchmark | gpt-oss-120b | Mistral Medium |
|---|---|---|
| LMArena Longer Query | 1319 | 1406 |
| Fiction.LiveBench | 44.4% | — |

## Writing & Preference

- gpt-oss-120b: 46.5 (#217)
- Mistral Medium: 60.0 (#103)

| Benchmark | gpt-oss-120b | Mistral Medium |
|---|---|---|
| LMArena Text | 1365 | 1424 |
| LMArena Creative Writing | 1275 | 1391 |
| Short-Story Creative Writing | 77.1% | 77.3% |
| LMArena Multi-Turn | 1340 | 1418 |
| EQ-Bench Creative Writing | 961 | — |
| WildBench | 84.5% | — |

## FAQ

### Is gpt-oss-120b better than Mistral Medium?

gpt-oss-120b and Mistral Medium score almost the same on the Noometry Index (36.3 vs 36.3), so choose on price, context window or the category you care about most.

### Which is cheaper, gpt-oss-120b or Mistral Medium?

gpt-oss-120b is cheaper. It lists at $0.037 per million input tokens and $0.17 per million output tokens; Mistral Medium lists at $1.50 and $7.50.

### Is gpt-oss-120b or Mistral Medium better for coding?

They score almost the same on coding (33.5 vs 34.2); test both on your own repository before choosing.

### Which has the bigger context window?

Mistral Medium does, with 262K tokens against 131K.

### How many benchmarks do gpt-oss-120b and Mistral Medium share?

29 benchmarks have published results for both models. gpt-oss-120b has 48 scored results on Noometry and Mistral Medium has 36.