Model comparison
GPT-5 Mini vs Mistral Small 3
GPT-5 Mini is the stronger model overall, scoring 41.8 to 31.2 on the Noometry Index. Mistral Small 3 costs 12× less per token, which makes it the better buy when GPT-5 Mini's lead doesn't matter for your workload.
Last verified . 22 shared benchmarks.
Mistral AISummary
- They share 22 benchmarks with published results for both. GPT-5 Mini scores higher in 8 categories and Mistral Small 3 in 0 categories; 8 gaps are clear of the uncertainty.
- The widest gap is in math, where GPT-5 Mini leads 46.7 to 16.3.
- The biggest single-benchmark swing is OTIS Mock AIME 2024-2025: 86.7% for GPT-5 Mini and 6.7% for Mistral Small 3.
- Mistral Small 3 is cheaper at $0.05 / $0.08 per million input/output tokens, against $0.25 / $2 for GPT-5 Mini.
- GPT-5 Mini accepts more context: 400K tokens versus 33K.
- Mistral Small 3 has downloadable open weights; the other is API-only.
Side by side
| GPT-5 Mini | Mistral Small 3 | |
|---|---|---|
| Provider | OpenAI | Mistral AI |
| Noometry Index | 41.8 | 31.2 |
| Released | 2025-08-07 | 2025-01-30 |
| Weights | Proprietary | Open |
| Context window | 400K | 33K |
| Max output | 128K | 16K |
| Input $ / M tokens | $0.25 | $0.05 |
| Output $ / M tokens | $2 | $0.08 |
| Results tracked | 60 | 24 |
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Category by category
Coding GPT-5 Mini leads
GPT-5 Mini: 40.1 (#146), Mistral Small 3: 36.5 (#207)
| Benchmark | GPT-5 Mini | Mistral Small 3 |
|---|---|---|
| LMArena Coding | 1406 | 1246 |
| SWE-bench Verified | 64.7% | — |
| SWE-bench Verified (bash only) | 59.8% | — |
| SWE-bench Multilingual | 39.7% | — |
| SciCode | 39.2% | — |
| WeirdML | 52.7% | — |
| BigCodeBench Instruct | — | 45.3% |
| BigCodeBench Complete | — | 50.4% |
| ALE-Bench | 799.77 | — |
| AlgoTune | 1.38 | — |
Agentic & Tool Use Not comparable
GPT-5 Mini: 31.1 (#70), Mistral Small 3: —
| Benchmark | GPT-5 Mini | Mistral Small 3 |
|---|---|---|
| Terminal-Bench | 34.8% | — |
| Berkeley Function Calling Leaderboard | 55.5% | — |
| Vending-Bench 2 | -31.18 | — |
Reasoning GPT-5 Mini leads
GPT-5 Mini: 23.9 (#168), Mistral Small 3: 18.9 (#273)
| Benchmark | GPT-5 Mini | Mistral Small 3 |
|---|---|---|
| Chess Puzzles | 30% | 0% |
| LMArena Hard Prompts | 1380 | 1233 |
| Epoch Capabilities Index | 145.52 | 127.07 |
| ARC-AGI-2 | 4.4% | — |
| Kagi LLM Benchmark | 70.3% | — |
| ARC-AGI-1 | 54.3% | — |
| CritPt | 0% | — |
| EnigmaEval | 8.2% | — |
| Mystery Game Puzzles | 10% | — |
| DTBench | 80.5% | — |
| LMCA | 34.2% | — |
| ForecastBench | 61 | — |
Math GPT-5 Mini leads
GPT-5 Mini: 46.7 (#69), Mistral Small 3: 16.3 (#295)
| Benchmark | GPT-5 Mini | Mistral Small 3 |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 86.7% | 6.7% |
| LMArena Math | 1378 | 1240 |
| FrontierMath (Tiers 1-3) | 46.7% | — |
| FrontierMath Tier 4 | 12.2% | — |
| ProofBench | 9% | — |
| Omni-MATH | 72.2% | — |
| MATH Level 5 | 97.8% | — |
| FrontierMath (Feb 2025 set) | 27.2% | — |
| FrontierMath Tier 4 (v1) | 6.3% | — |
Knowledge GPT-5 Mini leads
GPT-5 Mini: 45.6 (#86), Mistral Small 3: 25.1 (#263)
| Benchmark | GPT-5 Mini | Mistral Small 3 |
|---|---|---|
| GPQA Diamond | 75% | 47.3% |
| Confabulations | 13.3% | 25.2% |
| LMArena Expert | 1379 | 1202 |
| Humanity's Last Exam | 19.4% | — |
| SimpleQA Verified | 21.6% | — |
| MMLU-Pro | 83.5% | — |
| Vectara Hallucination Rate | 12.9% | — |
| GPQA (HELM) | 75.6% | — |
Multimodal Not comparable
GPT-5 Mini: 35.6 (#85), Mistral Small 3: —
| Benchmark | GPT-5 Mini | Mistral Small 3 |
|---|---|---|
| LMArena Vision | 1202 | — |
| VPCT | 40.2% | — |
Multilingual GPT-5 Mini leads
GPT-5 Mini: 48.9 (#137), Mistral Small 3: 37.3 (#236)
| Benchmark | GPT-5 Mini | Mistral Small 3 |
|---|---|---|
| LMArena Non-English | 1363 | 1198 |
| LMArena Chinese | 1385 | 1204 |
| LMArena French | 1386 | 1203 |
| LMArena German | 1366 | 1211 |
| LMArena Japanese | 1341 | 1111 |
| LMArena Korean | 1308 | 1188 |
| LMArena Russian | 1362 | 1216 |
| LMArena Spanish | 1355 | — |
Instruction Following GPT-5 Mini leads
GPT-5 Mini: 76.2 (#46), Mistral Small 3: 63.7 (#229)
| Benchmark | GPT-5 Mini | Mistral Small 3 |
|---|---|---|
| LMArena Instruction Following | 1357 | 1214 |
| IFEval | 92.7% | — |
Long Context GPT-5 Mini leads
GPT-5 Mini: 41.9 (#132), Mistral Small 3: 37.8 (#211)
| Benchmark | GPT-5 Mini | Mistral Small 3 |
|---|---|---|
| LMArena Longer Query | 1355 | 1246 |
| Fiction.LiveBench | 69.4% | — |
Writing & Preference GPT-5 Mini leads
GPT-5 Mini: 55.2 (#148), Mistral Small 3: 32.2 (#280)
| Benchmark | GPT-5 Mini | Mistral Small 3 |
|---|---|---|
| LMArena Text | 1373 | 1234 |
| LMArena Creative Writing | 1325 | 1195 |
| EQ-Bench Creative Writing | 1313 | 707 |
| LMArena Multi-Turn | 1363 | 1217 |
| Short-Story Creative Writing | 83.1% | — |
| WildBench | 85.5% | — |
Frequently asked questions
Is GPT-5 Mini better than Mistral Small 3?
GPT-5 Mini is the stronger model overall, scoring 41.8 to 31.2 on the Noometry Index. Mistral Small 3 costs 12× less per token, which makes it the better buy when GPT-5 Mini's lead doesn't matter for your workload.
Which is cheaper, GPT-5 Mini or Mistral Small 3?
Mistral Small 3 is cheaper. It lists at $0.05 per million input tokens and $0.08 per million output tokens; GPT-5 Mini lists at $0.25 and $2.
Is GPT-5 Mini or Mistral Small 3 better for coding?
GPT-5 Mini scores higher on coding benchmarks: 40.1 versus 36.5 in the Noometry coding category.
Which has the bigger context window?
GPT-5 Mini does, with 400K tokens against 33K.
How many benchmarks do GPT-5 Mini and Mistral Small 3 share?
22 benchmarks have published results for both models. GPT-5 Mini has 60 scored results on Noometry and Mistral Small 3 has 24.