Model comparison
GPT-5.4 nano vs Mixtral 8x7B
GPT-5.4 nano is the stronger model overall, scoring 41.9 to 26.8 on the Noometry Index.
Last verified . 21 shared benchmarks.
Mistral AISummary
- They share 21 benchmarks with published results for both. GPT-5.4 nano scores higher in 8 categories and Mixtral 8x7B in 0 categories; 8 gaps are clear of the uncertainty.
- The widest gap is in knowledge, where GPT-5.4 nano leads 41.8 to 11.0.
- The biggest single-benchmark swing is GPQA Diamond: 78.5% for GPT-5.4 nano and 30.6% for Mixtral 8x7B.
- GPT-5.4 nano is cheaper at $0.20 / $1.25 per million input/output tokens, against $0.70 / $0.70 for Mixtral 8x7B.
- GPT-5.4 nano accepts more context: 400K tokens versus 32K.
- Mixtral 8x7B has downloadable open weights; the other is API-only.
Side by side
| GPT-5.4 nano | Mixtral 8x7B | |
|---|---|---|
| Provider | OpenAI | Mistral AI |
| Noometry Index | 41.9 | 26.8 |
| Released | 2026-03-17 | 2023-12-11 |
| Weights | Proprietary | Open |
| Context window | 400K | 32K |
| Max output | 128K | 32K |
| Input $ / M tokens | $0.20 | $0.70 |
| Output $ / M tokens | $1.25 | $0.70 |
| Results tracked | 40 | 38 |
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Category by category
Coding GPT-5.4 nano leads
GPT-5.4 nano: 43.1 (#82), Mixtral 8x7B: 32.2 (#265)
| Benchmark | GPT-5.4 nano | Mixtral 8x7B |
|---|---|---|
| LMArena Coding | 1404 | 1127 |
| SciCode | 46.9% | — |
| WeirdML | 49.2% | — |
| ALE-Bench | 1,005 | — |
| HumanEval+ | — | 39.6% |
| MBPP+ | — | 49.7% |
Reasoning GPT-5.4 nano leads
GPT-5.4 nano: 23.8 (#159), Mixtral 8x7B: 17.4 (#283)
| Benchmark | GPT-5.4 nano | Mixtral 8x7B |
|---|---|---|
| LMArena Hard Prompts | 1380 | 1115 |
| DTBench | 80.3% | 49.6% |
| Epoch Capabilities Index | 145.78 | 118.38 |
| ForecastBench | 57.3 | 56.3 |
| ARC-AGI-2 | 5.7% | — |
| Kagi LLM Benchmark | 39.7% | — |
| ARC-AGI-1 | 51.5% | — |
| CritPt | 9.3% | — |
| Chess Puzzles | 30% | — |
| Mystery Game Puzzles | 9% | — |
| LMCA | 36.9% | — |
| Adversarial NLI | — | 55.2% |
| HellaSwag | — | 86.7% |
| PIQA | — | 83.6% |
| WinoGrande | — | 77.2% |
Math GPT-5.4 nano leads
GPT-5.4 nano: 40.7 (#76), Mixtral 8x7B: 17.2 (#284)
| Benchmark | GPT-5.4 nano | Mixtral 8x7B |
|---|---|---|
| LMArena Math | 1406 | 1147 |
| FrontierMath (Tiers 1-3) | 44.9% | — |
| FrontierMath Tier 4 | 12.2% | — |
| OTIS Mock AIME 2024-2025 | 87.8% | — |
| ProofBench | 5% | — |
| Omni-MATH | — | 10.5% |
| MATH Level 5 | — | 10% |
| FrontierMath (Feb 2025 set) | 25.9% | — |
| FrontierMath Tier 4 (v1) | 6.3% | — |
| GSM8K | — | 74.4% |
Knowledge GPT-5.4 nano leads
GPT-5.4 nano: 41.8 (#94), Mixtral 8x7B: 11.0 (#296)
| Benchmark | GPT-5.4 nano | Mixtral 8x7B |
|---|---|---|
| GPQA Diamond | 78.5% | 30.6% |
| LMArena Expert | 1397 | 1088 |
| SimpleQA Verified | 11.7% | — |
| MMLU-Pro | — | 33.5% |
| Vectara Hallucination Rate | 3.1% | — |
| GPQA (HELM) | — | 29.6% |
| ARC (AI2) Challenge | — | 87.3% |
| MMLU | — | 70.6% |
| OpenBookQA | — | 85.8% |
| TriviaQA | — | 82.2% |
Multimodal Not comparable
GPT-5.4 nano: 36.0 (#73), Mixtral 8x7B: —
| Benchmark | GPT-5.4 nano | Mixtral 8x7B |
|---|---|---|
| LMArena Vision | 1196 | — |
Multilingual GPT-5.4 nano leads
GPT-5.4 nano: 48.8 (#136), Mixtral 8x7B: 29.8 (#261)
| Benchmark | GPT-5.4 nano | Mixtral 8x7B |
|---|---|---|
| LMArena Non-English | 1359 | 1077 |
| LMArena Chinese | 1391 | 1055 |
| LMArena French | 1396 | 1165 |
| LMArena German | 1368 | 1114 |
| LMArena Japanese | 1342 | 931 |
| LMArena Korean | 1321 | 968 |
| LMArena Russian | 1363 | 1090 |
| LMArena Spanish | 1368 | 1110 |
Instruction Following GPT-5.4 nano leads
GPT-5.4 nano: 72.1 (#139), Mixtral 8x7B: 51.2 (#292)
| Benchmark | GPT-5.4 nano | Mixtral 8x7B |
|---|---|---|
| LMArena Instruction Following | 1362 | 1110 |
| IFEval | — | 57.5% |
Long Context GPT-5.4 nano leads
GPT-5.4 nano: 41.6 (#131), Mixtral 8x7B: 33.4 (#255)
| Benchmark | GPT-5.4 nano | Mixtral 8x7B |
|---|---|---|
| LMArena Longer Query | 1365 | 1103 |
Writing & Preference GPT-5.4 nano leads
GPT-5.4 nano: 55.9 (#137), Mixtral 8x7B: 34.4 (#265)
| Benchmark | GPT-5.4 nano | Mixtral 8x7B |
|---|---|---|
| LMArena Text | 1372 | 1132 |
| LMArena Creative Writing | 1313 | 1109 |
| LMArena Multi-Turn | 1382 | 1115 |
| WildBench | — | 67.3% |
Frequently asked questions
Is GPT-5.4 nano better than Mixtral 8x7B?
GPT-5.4 nano is the stronger model overall, scoring 41.9 to 26.8 on the Noometry Index.
Which is cheaper, GPT-5.4 nano or Mixtral 8x7B?
GPT-5.4 nano is cheaper. It lists at $0.20 per million input tokens and $1.25 per million output tokens; Mixtral 8x7B lists at $0.70 and $0.70.
Is GPT-5.4 nano or Mixtral 8x7B better for coding?
GPT-5.4 nano scores higher on coding benchmarks: 43.1 versus 32.2 in the Noometry coding category.
Which has the bigger context window?
GPT-5.4 nano does, with 400K tokens against 32K.
How many benchmarks do GPT-5.4 nano and Mixtral 8x7B share?
21 benchmarks have published results for both models. GPT-5.4 nano has 40 scored results on Noometry and Mixtral 8x7B has 38.