Model comparison
GPT-5.4 nano vs Mistral Small 3
GPT-5.4 nano is the stronger model overall, scoring 41.9 to 31.2 on the Noometry Index. Mistral Small 3 costs 8.0× less per token, which makes it the better buy when GPT-5.4 nano's lead doesn't matter for your workload.
Last verified . 20 shared benchmarks.
Mistral AISummary
- They share 20 benchmarks with published results for both. GPT-5.4 nano 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-5.4 nano leads 40.9 to 16.3.
- The biggest single-benchmark swing is OTIS Mock AIME 2024-2025: 87.8% for GPT-5.4 nano and 6.7% for Mistral Small 3.
- Mistral Small 3 is cheaper at $0.05 / $0.08 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 33K.
- Mistral Small 3 has downloadable open weights; the other is API-only.
Side by side
| GPT-5.4 nano | Mistral Small 3 | |
|---|---|---|
| Provider | OpenAI | Mistral AI |
| Noometry Index | 41.9 | 31.2 |
| Released | 2026-03-17 | 2025-01-30 |
| Weights | Proprietary | Open |
| Context window | 400K | 33K |
| Max output | 128K | 16K |
| Input $ / M tokens | $0.20 | $0.05 |
| Output $ / M tokens | $1.25 | $0.08 |
| Results tracked | 40 | 24 |
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Category by category
Coding GPT-5.4 nano leads
GPT-5.4 nano: 43.6 (#84), Mistral Small 3: 36.5 (#207)
| Benchmark | GPT-5.4 nano | Mistral Small 3 |
|---|---|---|
| LMArena Coding | 1405 | 1246 |
| SciCode | 46.9% | — |
| WeirdML | 49.2% | — |
| BigCodeBench Instruct | — | 45.3% |
| BigCodeBench Complete | — | 50.4% |
| ALE-Bench | 1,005 | — |
Reasoning GPT-5.4 nano leads
GPT-5.4 nano: 23.7 (#173), Mistral Small 3: 18.9 (#273)
| Benchmark | GPT-5.4 nano | Mistral Small 3 |
|---|---|---|
| Chess Puzzles | 30% | 0% |
| LMArena Hard Prompts | 1381 | 1233 |
| Epoch Capabilities Index | 145.81 | 127.07 |
| ARC-AGI-2 | 5.7% | — |
| Kagi LLM Benchmark | 39.7% | — |
| ARC-AGI-1 | 51.5% | — |
| CritPt | 9.3% | — |
| Mystery Game Puzzles | 9% | — |
| DTBench | 80.3% | — |
| LMCA | 36.9% | — |
| ForecastBench | 57.3 | — |
Math GPT-5.4 nano leads
GPT-5.4 nano: 40.9 (#88), Mistral Small 3: 16.3 (#295)
| Benchmark | GPT-5.4 nano | Mistral Small 3 |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 87.8% | 6.7% |
| LMArena Math | 1406 | 1240 |
| FrontierMath (Tiers 1-3) | 44.9% | — |
| FrontierMath Tier 4 | 12.2% | — |
| ProofBench | 5% | — |
| FrontierMath (Feb 2025 set) | 25.9% | — |
| FrontierMath Tier 4 (v1) | 6.3% | — |
Knowledge GPT-5.4 nano leads
GPT-5.4 nano: 41.9 (#103), Mistral Small 3: 25.1 (#263)
| Benchmark | GPT-5.4 nano | Mistral Small 3 |
|---|---|---|
| GPQA Diamond | 78.5% | 47.3% |
| LMArena Expert | 1396 | 1202 |
| SimpleQA Verified | 11.7% | — |
| Confabulations | — | 25.2% |
| Vectara Hallucination Rate | 3.1% | — |
Multimodal Not comparable
GPT-5.4 nano: 36.7 (#78), Mistral Small 3: —
| Benchmark | GPT-5.4 nano | Mistral Small 3 |
|---|---|---|
| LMArena Vision | 1196 | — |
Multilingual GPT-5.4 nano leads
GPT-5.4 nano: 48.6 (#140), Mistral Small 3: 37.3 (#236)
| Benchmark | GPT-5.4 nano | Mistral Small 3 |
|---|---|---|
| LMArena Non-English | 1359 | 1198 |
| LMArena Chinese | 1392 | 1204 |
| LMArena French | 1396 | 1203 |
| LMArena German | 1367 | 1211 |
| LMArena Japanese | 1343 | 1111 |
| LMArena Korean | 1320 | 1188 |
| LMArena Russian | 1363 | 1216 |
| LMArena Spanish | 1371 | — |
Instruction Following GPT-5.4 nano leads
GPT-5.4 nano: 71.9 (#144), Mistral Small 3: 63.7 (#229)
| Benchmark | GPT-5.4 nano | Mistral Small 3 |
|---|---|---|
| LMArena Instruction Following | 1362 | 1214 |
Long Context GPT-5.4 nano leads
GPT-5.4 nano: 41.6 (#137), Mistral Small 3: 37.8 (#211)
| Benchmark | GPT-5.4 nano | Mistral Small 3 |
|---|---|---|
| LMArena Longer Query | 1366 | 1246 |
Writing & Preference GPT-5.4 nano leads
GPT-5.4 nano: 55.7 (#142), Mistral Small 3: 32.2 (#280)
| Benchmark | GPT-5.4 nano | Mistral Small 3 |
|---|---|---|
| LMArena Text | 1372 | 1234 |
| LMArena Creative Writing | 1314 | 1195 |
| LMArena Multi-Turn | 1382 | 1217 |
| EQ-Bench Creative Writing | — | 707 |
Frequently asked questions
Is GPT-5.4 nano better than Mistral Small 3?
GPT-5.4 nano is the stronger model overall, scoring 41.9 to 31.2 on the Noometry Index. Mistral Small 3 costs 8.0× 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?
Mistral Small 3 is cheaper. It lists at $0.05 per million input tokens and $0.08 per million output tokens; GPT-5.4 nano lists at $0.20 and $1.25.
Is GPT-5.4 nano or Mistral Small 3 better for coding?
GPT-5.4 nano scores higher on coding benchmarks: 43.6 versus 36.5 in the Noometry coding category.
Which has the bigger context window?
GPT-5.4 nano does, with 400K tokens against 33K.
How many benchmarks do GPT-5.4 nano and Mistral Small 3 share?
20 benchmarks have published results for both models. GPT-5.4 nano has 40 scored results on Noometry and Mistral Small 3 has 24.