Model comparison
GPT-5.4 mini vs Mistral Small 3.1
GPT-5.4 mini is the stronger model overall, scoring 44.8 to 31.4 on the Noometry Index. Mistral Small 3.1 costs 4.2× less per token, which makes it the better buy when GPT-5.4 mini's lead doesn't matter for your workload.
Last verified . 23 shared benchmarks.
Mistral AISummary
- They share 23 benchmarks with published results for both. GPT-5.4 mini scores higher in 9 categories and Mistral Small 3.1 in 0 categories; 9 gaps are clear of the uncertainty.
- The widest gap is in math, where GPT-5.4 mini leads 45.4 to 13.7.
- The biggest single-benchmark swing is OTIS Mock AIME 2024-2025: 88.9% for GPT-5.4 mini and 3.9% for Mistral Small 3.1.
- Mistral Small 3.1 is cheaper at $0.35 / $0.56 per million input/output tokens, against $0.75 / $4.50 for GPT-5.4 mini.
- GPT-5.4 mini accepts more context: 400K tokens versus 128K.
- Mistral Small 3.1 has downloadable open weights; the other is API-only.
Side by side
| GPT-5.4 mini | Mistral Small 3.1 | |
|---|---|---|
| Provider | OpenAI | Mistral AI |
| Noometry Index | 44.8 | 31.4 |
| Released | 2026-03-17 | 2025-03-17 |
| Weights | Proprietary | Open |
| Context window | 400K | 128K |
| Max output | 128K | 102K |
| Input $ / M tokens | $0.75 | $0.35 |
| Output $ / M tokens | $4.50 | $0.56 |
| Results tracked | 46 | 28 |
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Category by category
Coding GPT-5.4 mini leads
GPT-5.4 mini: 45.0 (#67), Mistral Small 3.1: 37.7 (#175)
| Benchmark | GPT-5.4 mini | Mistral Small 3.1 |
|---|---|---|
| LMArena Coding | 1438 | 1309 |
| FrontierCode | 27% | — |
| LMArena WebDev | 1397 | — |
| SciCode | 49.9% | — |
| WeirdML | 60.3% | — |
| ALE-Bench | 1,189 | — |
Agentic & Tool Use Not comparable
GPT-5.4 mini: 29.6 (#74), Mistral Small 3.1: —
| Benchmark | GPT-5.4 mini | Mistral Small 3.1 |
|---|---|---|
| DeepResearch Bench | 36.3% | — |
Reasoning GPT-5.4 mini leads
GPT-5.4 mini: 30.3 (#77), Mistral Small 3.1: 18.9 (#249)
| Benchmark | GPT-5.4 mini | Mistral Small 3.1 |
|---|---|---|
| Chess Puzzles | 24% | 1% |
| LMArena Hard Prompts | 1424 | 1278 |
| Epoch Capabilities Index | 148.83 | 127.48 |
| ARC-AGI-2 | 18.9% | — |
| Kagi LLM Benchmark | 37.9% | — |
| NYT Connections (extended) | 61.8% | — |
| ARC-AGI-1 | 63.7% | — |
| CritPt | 10% | — |
| Thematic Generalization | 61.7% | — |
| Mystery Game Puzzles | 11% | — |
| DTBench | 80% | — |
| LMCA | 40.8% | — |
| ForecastBench | 57 | — |
Math GPT-5.4 mini leads
GPT-5.4 mini: 45.4 (#63), Mistral Small 3.1: 13.7 (#295)
| Benchmark | GPT-5.4 mini | Mistral Small 3.1 |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 88.9% | 3.9% |
| LMArena Math | 1418 | 1261 |
| FrontierMath (Tiers 1-3) | 51.2% | — |
| FrontierMath Tier 4 | 9.8% | — |
| ProofBench | 21% | — |
| Omni-MATH | — | 24.8% |
| FrontierMath (Feb 2025 set) | 28.3% | — |
| FrontierMath Tier 4 (v1) | 2.1% | — |
Knowledge GPT-5.4 mini leads
GPT-5.4 mini: 51.4 (#62), Mistral Small 3.1: 22.6 (#266)
| Benchmark | GPT-5.4 mini | Mistral Small 3.1 |
|---|---|---|
| GPQA Diamond | 86.9% | 41.9% |
| LMArena Expert | 1434 | 1258 |
| SimpleQA Verified | 29.4% | — |
| MMLU-Pro | — | 61% |
| Vectara Hallucination Rate | 5.5% | — |
| GPQA (HELM) | — | 39.2% |
Multimodal GPT-5.4 mini leads
GPT-5.4 mini: 39.0 (#51), Mistral Small 3.1: 32.6 (#93)
| Benchmark | GPT-5.4 mini | Mistral Small 3.1 |
|---|---|---|
| LMArena Vision | 1245 | 1136 |
Multilingual GPT-5.4 mini leads
GPT-5.4 mini: 52.1 (#94), Mistral Small 3.1: 41.4 (#204)
| Benchmark | GPT-5.4 mini | Mistral Small 3.1 |
|---|---|---|
| LMArena Non-English | 1405 | 1255 |
| LMArena Chinese | 1446 | 1254 |
| LMArena French | 1440 | 1270 |
| LMArena German | 1407 | 1266 |
| LMArena Japanese | 1375 | 1210 |
| LMArena Korean | 1369 | 1206 |
| LMArena Russian | 1417 | 1263 |
| LMArena Spanish | 1403 | 1283 |
Instruction Following GPT-5.4 mini leads
GPT-5.4 mini: 74.3 (#99), Mistral Small 3.1: 63.8 (#225)
| Benchmark | GPT-5.4 mini | Mistral Small 3.1 |
|---|---|---|
| LMArena Instruction Following | 1405 | 1264 |
| IFEval | — | 75% |
Long Context GPT-5.4 mini leads
GPT-5.4 mini: 42.9 (#107), Mistral Small 3.1: 39.5 (#172)
| Benchmark | GPT-5.4 mini | Mistral Small 3.1 |
|---|---|---|
| LMArena Longer Query | 1407 | 1300 |
Writing & Preference GPT-5.4 mini leads
GPT-5.4 mini: 64.2 (#56), Mistral Small 3.1: 37.2 (#254)
| Benchmark | GPT-5.4 mini | Mistral Small 3.1 |
|---|---|---|
| LMArena Text | 1411 | 1278 |
| LMArena Creative Writing | 1370 | 1253 |
| EQ-Bench Creative Writing | 1665 | 761 |
| LMArena Multi-Turn | 1429 | 1270 |
| WildBench | — | 78.8% |
Frequently asked questions
Is GPT-5.4 mini better than Mistral Small 3.1?
GPT-5.4 mini is the stronger model overall, scoring 44.8 to 31.4 on the Noometry Index. Mistral Small 3.1 costs 4.2× less per token, which makes it the better buy when GPT-5.4 mini's lead doesn't matter for your workload.
Which is cheaper, GPT-5.4 mini or Mistral Small 3.1?
Mistral Small 3.1 is cheaper. It lists at $0.35 per million input tokens and $0.56 per million output tokens; GPT-5.4 mini lists at $0.75 and $4.50.
Is GPT-5.4 mini or Mistral Small 3.1 better for coding?
GPT-5.4 mini scores higher on coding benchmarks: 45.0 versus 37.7 in the Noometry coding category.
Which has the bigger context window?
GPT-5.4 mini does, with 400K tokens against 128K.
How many benchmarks do GPT-5.4 mini and Mistral Small 3.1 share?
23 benchmarks have published results for both models. GPT-5.4 mini has 46 scored results on Noometry and Mistral Small 3.1 has 28.