Model comparison
GPT-5.4 nano vs Mistral Small 3.2
GPT-5.4 nano is the stronger model overall, scoring 41.9 to 30.8 on the Noometry Index. Mistral Small 3.2 costs 3.5× less per token, which makes it the better buy when GPT-5.4 nano's lead doesn't matter for your workload.
Last verified . 5 shared benchmarks.
Summary
- They share 5 benchmarks with published results for both. GPT-5.4 nano scores higher in 4 categories and Mistral Small 3.2 in 0 categories; 4 gaps are clear of the uncertainty.
- The widest gap is in math, where GPT-5.4 nano leads 40.7 to 24.9.
- The biggest single-benchmark swing is OTIS Mock AIME 2024-2025: 87.8% for GPT-5.4 nano and 30.3% for Mistral Small 3.2.
- Mistral Small 3.2 is cheaper at $0.0938 / $0.25 per million input/output tokens, against $0.20 / $1.25 for GPT-5.4 nano.
- GPT-5.4 nano accepts more context: 400K tokens versus 256K.
- Mistral Small 3.2 has downloadable open weights; the other is API-only.
Side by side
| GPT-5.4 nano | Mistral Small 3.2 | |
|---|---|---|
| Provider | OpenAI | Mistral AI |
| Noometry Index | 41.9 | 30.8 |
| Released | 2026-03-17 | 2025-06-20 |
| Weights | Proprietary | Open |
| Context window | 400K | 256K |
| Max output | 128K | 16K |
| Input $ / M tokens | $0.20 | $0.0938 |
| Output $ / M tokens | $1.25 | $0.25 |
| Results tracked | 40 | 6 |
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Category by category
Coding Not comparable
GPT-5.4 nano: 43.1 (#82), Mistral Small 3.2: —
| Benchmark | GPT-5.4 nano | Mistral Small 3.2 |
|---|---|---|
| SciCode | 46.9% | — |
| WeirdML | 49.2% | — |
| LMArena Coding | 1404 | — |
| ALE-Bench | 1,005 | — |
Reasoning GPT-5.4 nano leads
GPT-5.4 nano: 23.8 (#159), Mistral Small 3.2: 17.5 (#282)
| Benchmark | GPT-5.4 nano | Mistral Small 3.2 |
|---|---|---|
| Kagi LLM Benchmark | 39.7% | 40.4% |
| Chess Puzzles | 30% | 1% |
| Epoch Capabilities Index | 145.78 | 131.73 |
| ARC-AGI-2 | 5.7% | — |
| ARC-AGI-1 | 51.5% | — |
| CritPt | 9.3% | — |
| LMArena Hard Prompts | 1380 | — |
| Mystery Game Puzzles | 9% | — |
| DTBench | 80.3% | — |
| LMCA | 36.9% | — |
| ForecastBench | 57.3 | — |
Math GPT-5.4 nano leads
GPT-5.4 nano: 40.7 (#76), Mistral Small 3.2: 24.9 (#251)
| Benchmark | GPT-5.4 nano | Mistral Small 3.2 |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 87.8% | 30.3% |
| FrontierMath (Tiers 1-3) | 44.9% | — |
| FrontierMath Tier 4 | 12.2% | — |
| ProofBench | 5% | — |
| LMArena Math | 1406 | — |
| FrontierMath (Feb 2025 set) | 25.9% | — |
| FrontierMath Tier 4 (v1) | 6.3% | — |
Knowledge GPT-5.4 nano leads
GPT-5.4 nano: 41.8 (#94), Mistral Small 3.2: 26.8 (#249)
| Benchmark | GPT-5.4 nano | Mistral Small 3.2 |
|---|---|---|
| GPQA Diamond | 78.5% | 49.1% |
| SimpleQA Verified | 11.7% | — |
| Vectara Hallucination Rate | 3.1% | — |
| LMArena Expert | 1397 | — |
Multimodal Not comparable
GPT-5.4 nano: 36.0 (#73), Mistral Small 3.2: —
| Benchmark | GPT-5.4 nano | Mistral Small 3.2 |
|---|---|---|
| LMArena Vision | 1196 | — |
Multilingual Not comparable
GPT-5.4 nano: 48.8 (#136), Mistral Small 3.2: —
| Benchmark | GPT-5.4 nano | Mistral Small 3.2 |
|---|---|---|
| LMArena Non-English | 1359 | — |
| LMArena Chinese | 1391 | — |
| LMArena French | 1396 | — |
| LMArena German | 1368 | — |
| LMArena Japanese | 1342 | — |
| LMArena Korean | 1321 | — |
| LMArena Russian | 1363 | — |
| LMArena Spanish | 1368 | — |
Instruction Following Not comparable
GPT-5.4 nano: 72.1 (#139), Mistral Small 3.2: —
| Benchmark | GPT-5.4 nano | Mistral Small 3.2 |
|---|---|---|
| LMArena Instruction Following | 1362 | — |
Long Context Not comparable
GPT-5.4 nano: 41.6 (#131), Mistral Small 3.2: —
| Benchmark | GPT-5.4 nano | Mistral Small 3.2 |
|---|---|---|
| LMArena Longer Query | 1365 | — |
Writing & Preference GPT-5.4 nano leads
GPT-5.4 nano: 55.9 (#137), Mistral Small 3.2: 45.1 (#219)
| Benchmark | GPT-5.4 nano | Mistral Small 3.2 |
|---|---|---|
| LMArena Text | 1372 | — |
| LMArena Creative Writing | 1313 | — |
| EQ-Bench Creative Writing | — | 1255 |
| LMArena Multi-Turn | 1382 | — |
Frequently asked questions
Is GPT-5.4 nano better than Mistral Small 3.2?
GPT-5.4 nano is the stronger model overall, scoring 41.9 to 30.8 on the Noometry Index. Mistral Small 3.2 costs 3.5× less per token, which makes it the better buy when GPT-5.4 nano's lead doesn't matter for your workload.
Which is cheaper, GPT-5.4 nano or Mistral Small 3.2?
Mistral Small 3.2 is cheaper. It lists at $0.0938 per million input tokens and $0.25 per million output tokens; GPT-5.4 nano lists at $0.20 and $1.25.
Which has the bigger context window?
GPT-5.4 nano does, with 400K tokens against 256K.
How many benchmarks do GPT-5.4 nano and Mistral Small 3.2 share?
5 benchmarks have published results for both models. GPT-5.4 nano has 40 scored results on Noometry and Mistral Small 3.2 has 6.