# gpt-oss-20b vs Mistral Large

> gpt-oss-20b and Mistral Large score almost the same on the Noometry Index (32.5 vs 31.9), so choose on price, context window or the category you care about most.

- Canonical page: https://noometry.com/compare/gpt-oss-20b-vs-mistral-large
- Last updated: 2026-10-10
- Shared benchmarks: 30

## Summary

- They share 30 benchmarks with published results for both. gpt-oss-20b scores higher in 5 categories and Mistral Large in 4 categories; 8 gaps are clear of the uncertainty.
- The widest gap is in math, where gpt-oss-20b leads 39.4 to 18.2.
- The biggest single-benchmark swing is OTIS Mock AIME 2024-2025: 65.3% for gpt-oss-20b and 8.5% for Mistral Large.
- gpt-oss-20b is cheaper at $0.018 / $0.09 per million input/output tokens, against $2 / $6 for Mistral Large.

## Snapshot

| | gpt-oss-20b | Mistral Large |
|---|---|---|
| Provider | OpenAI | Mistral AI |
| Noometry Index | 32.5 | 31.9 |
| Rank | 255 | 263 |
| Context | 131K | 131K |
| Input $/M | $0.018 | $2 |
| Output $/M | $0.09 | $6 |
| Weights | Open | Open |

## Coding

- gpt-oss-20b: 37.6 (#192)
- Mistral Large: 34.3 (#240)

| Benchmark | gpt-oss-20b | Mistral Large |
|---|---|---|
| SciCode | 34.4% | 36.2% |
| LMArena Coding | 1306 | 1277 |
| ALE-Bench | 566.05 | 264.7 |
| WeirdML | 40.9% | — |
| BigCodeBench Instruct | — | 30% |
| LiveBench Coding | — | 47.1% |
| BigCodeBench Complete | — | 38.3% |
| HumanEval+ | — | 62.2% |
| MBPP+ | — | 59.5% |

## Agentic & Tool Use

- gpt-oss-20b: 9.3 (#154)
- Mistral Large: 28.6 (#89)

| Benchmark | gpt-oss-20b | Mistral Large |
|---|---|---|
| Terminal-Bench | 3.4% | — |
| Berkeley Function Calling Leaderboard | — | 38.4% |

## Reasoning

- gpt-oss-20b: 19.3 (#261)
- Mistral Large: 15.8 (#310)

| Benchmark | gpt-oss-20b | Mistral Large |
|---|---|---|
| CritPt | 1.4% | 0% |
| LMArena Hard Prompts | 1274 | 1257 |
| DTBench | 68% | 65.1% |
| LMCA | 14.5% | 16.7% |
| Epoch Capabilities Index | 137.82 | 128.52 |
| SimpleBench | — | 22.5% |
| Kagi LLM Benchmark | 53.2% | — |
| Chess Puzzles | 4% | — |
| LiveBench Reasoning | — | 43.5% |
| LiveBench Data Analysis | — | 50.1% |
| ForecastBench | — | 57.1 |
| LiveBench | — | 48.4% |

## Math

- gpt-oss-20b: 39.4 (#103)
- Mistral Large: 18.2 (#291)

| Benchmark | gpt-oss-20b | Mistral Large |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 65.3% | 8.5% |
| Omni-MATH | 56.5% | 28.1% |
| LMArena Math | 1317 | 1262 |
| LiveBench Math | — | 42.5% |
| MATH Level 5 | — | 50.3% |
| FrontierMath (Feb 2025 set) | — | 0.3% |

## Knowledge

- gpt-oss-20b: 34.6 (#195)
- Mistral Large: 30.1 (#230)

| Benchmark | gpt-oss-20b | Mistral Large |
|---|---|---|
| GPQA Diamond | 60.8% | 51.3% |
| MMLU-Pro | 74% | 59.9% |
| GPQA (HELM) | 59.4% | 43.5% |
| LMArena Expert | 1258 | 1232 |
| Confabulations | — | 21.4% |
| Vectara Hallucination Rate | — | 4.5% |
| MMLU | — | 80% |

## Multilingual

- gpt-oss-20b: 42.2 (#197)
- Mistral Large: 40.0 (#219)

| Benchmark | gpt-oss-20b | Mistral Large |
|---|---|---|
| LMArena Non-English | 1268 | 1237 |
| LMArena Chinese | 1314 | 1240 |
| LMArena German | 1255 | 1254 |
| LMArena Japanese | 1244 | 1188 |
| LMArena Korean | 1236 | 1202 |
| LMArena Russian | 1278 | 1257 |
| LMArena Spanish | 1267 | 1268 |
| LMArena French | — | 1325 |

## Instruction Following

- gpt-oss-20b: 61.8 (#240)
- Mistral Large: 67.9 (#191)

| Benchmark | gpt-oss-20b | Mistral Large |
|---|---|---|
| IFEval | 73.2% | 87.7% |
| LMArena Instruction Following | 1236 | 1249 |
| LiveBench Instruction Following | — | 67.9% |

## Long Context

- gpt-oss-20b: 37.9 (#209)
- Mistral Large: 38.3 (#199)

| Benchmark | gpt-oss-20b | Mistral Large |
|---|---|---|
| LMArena Longer Query | 1250 | 1261 |

## Writing & Preference

- gpt-oss-20b: 35.5 (#265)
- Mistral Large: 40.7 (#242)

| Benchmark | gpt-oss-20b | Mistral Large |
|---|---|---|
| LMArena Text | 1287 | 1266 |
| LMArena Creative Writing | 1201 | 1243 |
| EQ-Bench Creative Writing | 666 | 985 |
| WildBench | 73.7% | 80.1% |
| LMArena Multi-Turn | 1268 | 1260 |
| Short-Story Creative Writing | — | 69% |
| LiveBench Language | — | 39.4% |

## FAQ

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

gpt-oss-20b and Mistral Large score almost the same on the Noometry Index (32.5 vs 31.9), so choose on price, context window or the category you care about most.

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

gpt-oss-20b is cheaper. It lists at $0.018 per million input tokens and $0.09 per million output tokens; Mistral Large lists at $2 and $6.

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

gpt-oss-20b scores higher on coding benchmarks: 37.6 versus 34.3 in the Noometry coding category.

### Which has the bigger context window?

Both accept 131K tokens.

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

30 benchmarks have published results for both models. gpt-oss-20b has 34 scored results on Noometry and Mistral Large has 51.