Model comparison
gpt-oss-20b vs Mistral Large 3
Mistral Large 3 is the stronger model overall, scoring 39.1 to 32.5 on the Noometry Index. gpt-oss-20b costs 10× less per token, which makes it the better buy when Mistral Large 3's lead doesn't matter for your workload.
Last verified . 18 shared benchmarks.
Mistral AISummary
- They share 18 benchmarks with published results for both. gpt-oss-20b scores higher in 3 categories and Mistral Large 3 in 5 categories; 7 gaps are clear of the uncertainty.
- The widest gap is in writing & preference, where Mistral Large 3 leads 60.0 to 35.5.
- gpt-oss-20b is cheaper at $0.018 / $0.09 per million input/output tokens, against $0.25 / $0.75 for Mistral Large 3.
- Mistral Large 3 accepts more context: 262K tokens versus 131K.
Side by side
| gpt-oss-20b | Mistral Large 3 | |
|---|---|---|
| Provider | OpenAI | Mistral AI |
| Noometry Index | 32.5 | 39.1 |
| Released | 2025-08-05 | 2025-12-02 |
| Weights | Open | Open |
| Context window | 131K | 262K |
| Max output | 16K | 8K |
| Input $ / M tokens | $0.018 | $0.25 |
| Output $ / M tokens | $0.09 | $0.75 |
| Results tracked | 34 | 24 |
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Category by category
Coding gpt-oss-20b leads
gpt-oss-20b: 37.6 (#192), Mistral Large 3: 34.4 (#237)
| Benchmark | gpt-oss-20b | Mistral Large 3 |
|---|---|---|
| LMArena Coding | 1306 | 1448 |
| LMArena WebDev | — | 1230 |
| SciCode | 34.4% | — |
| WeirdML | 40.9% | — |
| ALE-Bench | 566.05 | — |
Agentic & Tool Use Not comparable
gpt-oss-20b: 9.3 (#154), Mistral Large 3: —
| Benchmark | gpt-oss-20b | Mistral Large 3 |
|---|---|---|
| Terminal-Bench | 3.4% | — |
Reasoning gpt-oss-20b leads
gpt-oss-20b: 19.3 (#261), Mistral Large 3: 15.2 (#319)
| Benchmark | gpt-oss-20b | Mistral Large 3 |
|---|---|---|
| Kagi LLM Benchmark | 53.2% | 50.9% |
| LMArena Hard Prompts | 1274 | 1429 |
| NYT Connections (extended) | — | 7.5% |
| CritPt | 1.4% | — |
| Chess Puzzles | 4% | — |
| Thematic Generalization | — | 23% |
| DTBench | 68% | — |
| LMCA | 14.5% | — |
| Epoch Capabilities Index | 137.82 | — |
Math Too close to call
gpt-oss-20b: 39.4 (#103), Mistral Large 3: 38.7 (#129)
| Benchmark | gpt-oss-20b | Mistral Large 3 |
|---|---|---|
| LMArena Math | 1317 | 1414 |
| OTIS Mock AIME 2024-2025 | 65.3% | — |
| Omni-MATH | 56.5% | — |
Knowledge Mistral Large 3 leads
gpt-oss-20b: 34.6 (#195), Mistral Large 3: 36.0 (#177)
| Benchmark | gpt-oss-20b | Mistral Large 3 |
|---|---|---|
| LMArena Expert | 1258 | 1421 |
| GPQA Diamond | 60.8% | — |
| MMLU-Pro | 74% | — |
| Vectara Hallucination Rate | — | 14.5% |
| GPQA (HELM) | 59.4% | — |
Multimodal Not comparable
gpt-oss-20b: —, Mistral Large 3: 38.2 (#66)
| Benchmark | gpt-oss-20b | Mistral Large 3 |
|---|---|---|
| LMArena Vision | — | 1221 |
Multilingual Mistral Large 3 leads
gpt-oss-20b: 42.2 (#197), Mistral Large 3: 52.5 (#84)
| Benchmark | gpt-oss-20b | Mistral Large 3 |
|---|---|---|
| LMArena Non-English | 1268 | 1413 |
| LMArena Chinese | 1314 | 1447 |
| LMArena German | 1255 | 1437 |
| LMArena Japanese | 1244 | 1394 |
| LMArena Korean | 1236 | 1384 |
| LMArena Russian | 1278 | 1411 |
| LMArena Spanish | 1267 | 1440 |
| LMArena French | — | 1455 |
Instruction Following Mistral Large 3 leads
gpt-oss-20b: 61.8 (#240), Mistral Large 3: 74.0 (#108)
| Benchmark | gpt-oss-20b | Mistral Large 3 |
|---|---|---|
| LMArena Instruction Following | 1236 | 1403 |
| IFEval | 73.2% | — |
Long Context Mistral Large 3 leads
gpt-oss-20b: 37.9 (#209), Mistral Large 3: 43.1 (#105)
| Benchmark | gpt-oss-20b | Mistral Large 3 |
|---|---|---|
| LMArena Longer Query | 1250 | 1413 |
Writing & Preference Mistral Large 3 leads
gpt-oss-20b: 35.5 (#265), Mistral Large 3: 60.0 (#101)
| Benchmark | gpt-oss-20b | Mistral Large 3 |
|---|---|---|
| LMArena Text | 1287 | 1428 |
| LMArena Creative Writing | 1201 | 1386 |
| EQ-Bench Creative Writing | 666 | 1412 |
| LMArena Multi-Turn | 1268 | 1429 |
| WildBench | 73.7% | — |
Frequently asked questions
Is gpt-oss-20b better than Mistral Large 3?
Mistral Large 3 is the stronger model overall, scoring 39.1 to 32.5 on the Noometry Index. gpt-oss-20b costs 10× less per token, which makes it the better buy when Mistral Large 3's lead doesn't matter for your workload.
Which is cheaper, gpt-oss-20b or Mistral Large 3?
gpt-oss-20b is cheaper. It lists at $0.018 per million input tokens and $0.09 per million output tokens; Mistral Large 3 lists at $0.25 and $0.75.
Is gpt-oss-20b or Mistral Large 3 better for coding?
gpt-oss-20b scores higher on coding benchmarks: 37.6 versus 34.4 in the Noometry coding category.
Which has the bigger context window?
Mistral Large 3 does, with 262K tokens against 131K.
How many benchmarks do gpt-oss-20b and Mistral Large 3 share?
18 benchmarks have published results for both models. gpt-oss-20b has 34 scored results on Noometry and Mistral Large 3 has 24.