# gpt-oss-20b vs Mistral Medium

> Mistral Medium is the stronger model overall, scoring 36.3 to 32.5 on the Noometry Index. gpt-oss-20b costs 83× less per token, which makes it the better buy when Mistral Medium's lead doesn't matter for your workload.

- Canonical page: https://noometry.com/compare/gpt-oss-20b-vs-mistral-medium
- Last updated: 2026-10-11
- Shared benchmarks: 25

## Summary

- They share 25 benchmarks with published results for both. gpt-oss-20b scores higher in 3 categories and Mistral Medium in 6 categories; 9 gaps are clear of the uncertainty.
- The widest gap is in writing & preference, where Mistral Medium leads 60.0 to 35.5.
- The biggest single-benchmark swing is OTIS Mock AIME 2024-2025: 65.3% for gpt-oss-20b and 32.2% for Mistral Medium.
- gpt-oss-20b is cheaper at $0.018 / $0.09 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-20b | Mistral Medium |
|---|---|---|
| Provider | OpenAI | Mistral AI |
| Noometry Index | 32.5 | 36.3 |
| Rank | 255 | 218 |
| Context | 131K | 262K |
| Input $/M | $0.018 | $1.50 |
| Output $/M | $0.09 | $7.50 |
| Weights | Open | Open |

## Coding

- gpt-oss-20b: 37.6 (#192)
- Mistral Medium: 34.2 (#243)

| Benchmark | gpt-oss-20b | Mistral Medium |
|---|---|---|
| SciCode | 34.4% | 40.2% |
| WeirdML | 40.9% | 43.7% |
| LMArena Coding | 1306 | 1434 |
| ALE-Bench | 566.05 | 763.98 |
| FrontierCode | — | 8% |

## Agentic & Tool Use

- gpt-oss-20b: 9.3 (#154)
- Mistral Medium: 28.3 (#90)

| Benchmark | gpt-oss-20b | Mistral Medium |
|---|---|---|
| Terminal-Bench | 3.4% | — |
| Berkeley Function Calling Leaderboard | — | 37.7% |

## Reasoning

- gpt-oss-20b: 19.3 (#261)
- Mistral Medium: 24.0 (#167)

| Benchmark | gpt-oss-20b | Mistral Medium |
|---|---|---|
| Kagi LLM Benchmark | 53.2% | 50% |
| CritPt | 1.4% | 0% |
| LMArena Hard Prompts | 1274 | 1426 |
| DTBench | 68% | 75.5% |
| LMCA | 14.5% | 26.1% |
| Chess Puzzles | 4% | — |
| Surface Evolver Bench | — | 26.9% |
| Epoch Capabilities Index | 137.82 | — |

## Math

- gpt-oss-20b: 39.4 (#103)
- Mistral Medium: 28.1 (#245)

| Benchmark | gpt-oss-20b | Mistral Medium |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 65.3% | 32.2% |
| LMArena Math | 1317 | 1408 |
| ProofBench | — | 9% |
| Omni-MATH | 56.5% | — |
| MATH Level 5 | — | 81.6% |
| FrontierMath (Feb 2025 set) | — | 0.3% |

## Knowledge

- gpt-oss-20b: 34.6 (#195)
- Mistral Medium: 25.0 (#265)

| Benchmark | gpt-oss-20b | Mistral Medium |
|---|---|---|
| GPQA Diamond | 60.8% | 59.5% |
| LMArena Expert | 1258 | 1408 |
| Humanity's Last Exam | — | 4.5% |
| MMLU-Pro | 74% | — |
| Vectara Hallucination Rate | — | 22.7% |
| GPQA (HELM) | 59.4% | — |

## Multimodal

- gpt-oss-20b: —
- Mistral Medium: 35.3 (#88)

| Benchmark | gpt-oss-20b | Mistral Medium |
|---|---|---|
| LMArena Vision | — | 1172 |

## Multilingual

- gpt-oss-20b: 42.2 (#197)
- Mistral Medium: 52.1 (#91)

| Benchmark | gpt-oss-20b | Mistral Medium |
|---|---|---|
| LMArena Non-English | 1268 | 1408 |
| LMArena Chinese | 1314 | 1447 |
| LMArena German | 1255 | 1432 |
| LMArena Japanese | 1244 | 1378 |
| LMArena Korean | 1236 | 1380 |
| LMArena Russian | 1278 | 1411 |
| LMArena Spanish | 1267 | 1433 |
| LMArena French | — | 1459 |

## Instruction Following

- gpt-oss-20b: 61.8 (#240)
- Mistral Medium: 73.7 (#116)

| Benchmark | gpt-oss-20b | Mistral Medium |
|---|---|---|
| LMArena Instruction Following | 1236 | 1398 |
| IFEval | 73.2% | — |

## Long Context

- gpt-oss-20b: 37.9 (#209)
- Mistral Medium: 42.9 (#114)

| Benchmark | gpt-oss-20b | Mistral Medium |
|---|---|---|
| LMArena Longer Query | 1250 | 1406 |

## Writing & Preference

- gpt-oss-20b: 35.5 (#265)
- Mistral Medium: 60.0 (#103)

| Benchmark | gpt-oss-20b | Mistral Medium |
|---|---|---|
| LMArena Text | 1287 | 1424 |
| LMArena Creative Writing | 1201 | 1391 |
| LMArena Multi-Turn | 1268 | 1418 |
| Short-Story Creative Writing | — | 77.3% |
| EQ-Bench Creative Writing | 666 | — |
| WildBench | 73.7% | — |

## FAQ

### Is gpt-oss-20b better than Mistral Medium?

Mistral Medium is the stronger model overall, scoring 36.3 to 32.5 on the Noometry Index. gpt-oss-20b costs 83× less per token, which makes it the better buy when Mistral Medium's lead doesn't matter for your workload.

### Which is cheaper, gpt-oss-20b or Mistral Medium?

gpt-oss-20b is cheaper. It lists at $0.018 per million input tokens and $0.09 per million output tokens; Mistral Medium lists at $1.50 and $7.50.

### Is gpt-oss-20b or Mistral Medium better for coding?

gpt-oss-20b scores higher on coding benchmarks: 37.6 versus 34.2 in the Noometry coding category.

### Which has the bigger context window?

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

### How many benchmarks do gpt-oss-20b and Mistral Medium share?

25 benchmarks have published results for both models. gpt-oss-20b has 34 scored results on Noometry and Mistral Medium has 36.