Model comparison
gpt-oss-20b vs Mistral Small 3.1
gpt-oss-20b and Mistral Small 3.1 score almost the same on the Noometry Index (32.5 vs 31.7), so choose on price, context window or the category you care about most.
Last verified . 26 shared benchmarks.
Mistral AISummary
- They share 26 benchmarks with published results for both. gpt-oss-20b scores higher in 3 categories and Mistral Small 3.1 in 5 categories; 5 gaps are clear of the uncertainty.
- The widest gap is in math, where gpt-oss-20b leads 39.4 to 14.7.
- The biggest single-benchmark swing is OTIS Mock AIME 2024-2025: 65.3% for gpt-oss-20b and 3.9% for Mistral Small 3.1.
- gpt-oss-20b is cheaper at $0.018 / $0.09 per million input/output tokens, against $0.35 / $0.56 for Mistral Small 3.1.
- gpt-oss-20b accepts more context: 131K tokens versus 128K.
Side by side
| gpt-oss-20b | Mistral Small 3.1 | |
|---|---|---|
| Provider | OpenAI | Mistral AI |
| Noometry Index | 32.5 | 31.7 |
| Released | 2025-08-05 | 2025-03-17 |
| Weights | Open | Open |
| Context window | 131K | 128K |
| Max output | 16K | 102K |
| Input $ / M tokens | $0.018 | $0.35 |
| Output $ / M tokens | $0.09 | $0.56 |
| Results tracked | 34 | 28 |
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Category by category
Coding Too close to call
gpt-oss-20b: 37.6 (#192), Mistral Small 3.1: 38.3 (#179)
| Benchmark | gpt-oss-20b | Mistral Small 3.1 |
|---|---|---|
| LMArena Coding | 1306 | 1309 |
| SciCode | 34.4% | — |
| WeirdML | 40.9% | — |
| ALE-Bench | 566.05 | — |
Agentic & Tool Use Not comparable
gpt-oss-20b: 9.3 (#154), Mistral Small 3.1: —
| Benchmark | gpt-oss-20b | Mistral Small 3.1 |
|---|---|---|
| Terminal-Bench | 3.4% | — |
Reasoning Too close to call
gpt-oss-20b: 19.3 (#261), Mistral Small 3.1: 19.7 (#254)
| Benchmark | gpt-oss-20b | Mistral Small 3.1 |
|---|---|---|
| Chess Puzzles | 4% | 1% |
| LMArena Hard Prompts | 1274 | 1278 |
| Epoch Capabilities Index | 137.82 | 127.48 |
| Kagi LLM Benchmark | 53.2% | — |
| CritPt | 1.4% | — |
| DTBench | 68% | — |
| LMCA | 14.5% | — |
Math gpt-oss-20b leads
gpt-oss-20b: 39.4 (#103), Mistral Small 3.1: 14.7 (#301)
| Benchmark | gpt-oss-20b | Mistral Small 3.1 |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 65.3% | 3.9% |
| Omni-MATH | 56.5% | 24.8% |
| LMArena Math | 1317 | 1262 |
Knowledge gpt-oss-20b leads
gpt-oss-20b: 34.6 (#195), Mistral Small 3.1: 22.6 (#271)
| Benchmark | gpt-oss-20b | Mistral Small 3.1 |
|---|---|---|
| GPQA Diamond | 60.8% | 41.9% |
| MMLU-Pro | 74% | 61% |
| GPQA (HELM) | 59.4% | 39.2% |
| LMArena Expert | 1258 | 1257 |
Multimodal Not comparable
gpt-oss-20b: —, Mistral Small 3.1: 33.2 (#99)
| Benchmark | gpt-oss-20b | Mistral Small 3.1 |
|---|---|---|
| LMArena Vision | — | 1136 |
Multilingual Too close to call
gpt-oss-20b: 42.2 (#197), Mistral Small 3.1: 41.2 (#209)
| Benchmark | gpt-oss-20b | Mistral Small 3.1 |
|---|---|---|
| LMArena Non-English | 1268 | 1255 |
| LMArena Chinese | 1314 | 1253 |
| LMArena German | 1255 | 1266 |
| LMArena Japanese | 1244 | 1208 |
| LMArena Korean | 1236 | 1206 |
| LMArena Russian | 1278 | 1263 |
| LMArena Spanish | 1267 | 1283 |
| LMArena French | — | 1273 |
Instruction Following Mistral Small 3.1 leads
gpt-oss-20b: 61.8 (#240), Mistral Small 3.1: 63.6 (#230)
| Benchmark | gpt-oss-20b | Mistral Small 3.1 |
|---|---|---|
| IFEval | 73.2% | 75% |
| LMArena Instruction Following | 1236 | 1264 |
Long Context Mistral Small 3.1 leads
gpt-oss-20b: 37.9 (#209), Mistral Small 3.1: 39.5 (#178)
| Benchmark | gpt-oss-20b | Mistral Small 3.1 |
|---|---|---|
| LMArena Longer Query | 1250 | 1299 |
Writing & Preference Mistral Small 3.1 leads
gpt-oss-20b: 35.5 (#265), Mistral Small 3.1: 37.0 (#259)
| Benchmark | gpt-oss-20b | Mistral Small 3.1 |
|---|---|---|
| LMArena Text | 1287 | 1277 |
| LMArena Creative Writing | 1201 | 1253 |
| EQ-Bench Creative Writing | 666 | 761 |
| WildBench | 73.7% | 78.8% |
| LMArena Multi-Turn | 1268 | 1270 |
Frequently asked questions
Is gpt-oss-20b better than Mistral Small 3.1?
gpt-oss-20b and Mistral Small 3.1 score almost the same on the Noometry Index (32.5 vs 31.7), so choose on price, context window or the category you care about most.
Which is cheaper, gpt-oss-20b or Mistral Small 3.1?
gpt-oss-20b is cheaper. It lists at $0.018 per million input tokens and $0.09 per million output tokens; Mistral Small 3.1 lists at $0.35 and $0.56.
Is gpt-oss-20b or Mistral Small 3.1 better for coding?
They score almost the same on coding (37.6 vs 38.3); test both on your own repository before choosing.
Which has the bigger context window?
gpt-oss-20b does, with 131K tokens against 128K.
How many benchmarks do gpt-oss-20b and Mistral Small 3.1 share?
26 benchmarks have published results for both models. gpt-oss-20b has 34 scored results on Noometry and Mistral Small 3.1 has 28.