Model comparison
GPT-5.4 nano vs Mistral Small
GPT-5.4 nano is the stronger model overall, scoring 41.9 to 33.4 on the Noometry Index. Mistral Small costs 1.8× less per token, which makes it the better buy when GPT-5.4 nano's lead doesn't matter for your workload.
Last verified . 27 shared benchmarks.
Mistral AISummary
- They share 27 benchmarks with published results for both. GPT-5.4 nano scores higher in 9 categories and Mistral Small in 0 categories; 9 gaps are clear of the uncertainty.
- The widest gap is in math, where GPT-5.4 nano leads 40.9 to 16.4.
- The biggest single-benchmark swing is OTIS Mock AIME 2024-2025: 87.8% for GPT-5.4 nano and 5.8% for Mistral Small.
- Mistral Small is cheaper at $0.15 / $0.60 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 262K.
- Mistral Small has downloadable open weights; the other is API-only.
Side by side
| GPT-5.4 nano | Mistral Small | |
|---|---|---|
| Provider | OpenAI | Mistral AI |
| Noometry Index | 41.9 | 33.4 |
| Released | 2026-03-17 | 2024-02-26 |
| Weights | Proprietary | Open |
| Context window | 400K | 262K |
| Max output | 128K | 256K |
| Input $ / M tokens | $0.20 | $0.15 |
| Output $ / M tokens | $1.25 | $0.60 |
| Results tracked | 40 | 39 |
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Category by category
Coding GPT-5.4 nano leads
GPT-5.4 nano: 43.6 (#84), Mistral Small: 34.0 (#247)
| Benchmark | GPT-5.4 nano | Mistral Small |
|---|---|---|
| SciCode | 46.9% | 26.5% |
| LMArena Coding | 1405 | 1362 |
| ALE-Bench | 1,005 | 497.62 |
| WeirdML | 49.2% | — |
| BigCodeBench Instruct | — | 36.1% |
| LiveBench Coding | — | 36.2% |
| BigCodeBench Complete | — | 46.6% |
Agentic & Tool Use Not comparable
GPT-5.4 nano: —, Mistral Small: 28.1 (#93)
| Benchmark | GPT-5.4 nano | Mistral Small |
|---|---|---|
| Berkeley Function Calling Leaderboard | — | 37.1% |
Reasoning GPT-5.4 nano leads
GPT-5.4 nano: 23.7 (#173), Mistral Small: 19.8 (#250)
| Benchmark | GPT-5.4 nano | Mistral Small |
|---|---|---|
| Kagi LLM Benchmark | 39.7% | 37.8% |
| CritPt | 9.3% | 0% |
| LMArena Hard Prompts | 1381 | 1335 |
| DTBench | 80.3% | 70.9% |
| LMCA | 36.9% | 20.6% |
| ARC-AGI-2 | 5.7% | — |
| ARC-AGI-1 | 51.5% | — |
| Chess Puzzles | 30% | — |
| LiveBench Reasoning | — | 44.8% |
| Mystery Game Puzzles | 9% | — |
| LiveBench Data Analysis | — | 53.7% |
| Epoch Capabilities Index | 145.81 | — |
| ForecastBench | 57.3 | — |
| LiveBench | — | 44% |
Math GPT-5.4 nano leads
GPT-5.4 nano: 40.9 (#88), Mistral Small: 16.4 (#293)
| Benchmark | GPT-5.4 nano | Mistral Small |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 87.8% | 5.8% |
| LMArena Math | 1406 | 1341 |
| FrontierMath (Tiers 1-3) | 44.9% | — |
| FrontierMath Tier 4 | 12.2% | — |
| ProofBench | 5% | — |
| LiveBench Math | — | 39.9% |
| MATH Level 5 | — | 46.8% |
| 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: 31.0 (#222)
| Benchmark | GPT-5.4 nano | Mistral Small |
|---|---|---|
| GPQA Diamond | 78.5% | 47.5% |
| Vectara Hallucination Rate | 3.1% | 5.1% |
| LMArena Expert | 1396 | 1291 |
| SimpleQA Verified | 11.7% | — |
| MMLU | — | 68.7% |
Multimodal GPT-5.4 nano leads
GPT-5.4 nano: 36.7 (#78), Mistral Small: 33.5 (#96)
| Benchmark | GPT-5.4 nano | Mistral Small |
|---|---|---|
| LMArena Vision | 1196 | 1142 |
Multilingual GPT-5.4 nano leads
GPT-5.4 nano: 48.6 (#140), Mistral Small: 45.5 (#169)
| Benchmark | GPT-5.4 nano | Mistral Small |
|---|---|---|
| LMArena Non-English | 1359 | 1315 |
| LMArena Chinese | 1392 | 1340 |
| LMArena French | 1396 | 1337 |
| LMArena German | 1367 | 1340 |
| LMArena Japanese | 1343 | 1275 |
| LMArena Korean | 1320 | 1259 |
| LMArena Russian | 1363 | 1324 |
| LMArena Spanish | 1371 | 1346 |
Instruction Following GPT-5.4 nano leads
GPT-5.4 nano: 71.9 (#144), Mistral Small: 66.4 (#209)
| Benchmark | GPT-5.4 nano | Mistral Small |
|---|---|---|
| LMArena Instruction Following | 1362 | 1310 |
| LiveBench Instruction Following | — | 63.7% |
Long Context GPT-5.4 nano leads
GPT-5.4 nano: 41.6 (#137), Mistral Small: 40.4 (#156)
| Benchmark | GPT-5.4 nano | Mistral Small |
|---|---|---|
| LMArena Longer Query | 1366 | 1327 |
Writing & Preference GPT-5.4 nano leads
GPT-5.4 nano: 55.7 (#142), Mistral Small: 52.5 (#171)
| Benchmark | GPT-5.4 nano | Mistral Small |
|---|---|---|
| LMArena Text | 1372 | 1338 |
| LMArena Creative Writing | 1314 | 1305 |
| LMArena Multi-Turn | 1382 | 1344 |
| LiveBench Language | — | 30.5% |
Frequently asked questions
Is GPT-5.4 nano better than Mistral Small?
GPT-5.4 nano is the stronger model overall, scoring 41.9 to 33.4 on the Noometry Index. Mistral Small costs 1.8× 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?
Mistral Small is cheaper. It lists at $0.15 per million input tokens and $0.60 per million output tokens; GPT-5.4 nano lists at $0.20 and $1.25.
Is GPT-5.4 nano or Mistral Small better for coding?
GPT-5.4 nano scores higher on coding benchmarks: 43.6 versus 34.0 in the Noometry coding category.
Which has the bigger context window?
GPT-5.4 nano does, with 400K tokens against 262K.
How many benchmarks do GPT-5.4 nano and Mistral Small share?
27 benchmarks have published results for both models. GPT-5.4 nano has 40 scored results on Noometry and Mistral Small has 39.