Model comparison
Codestral vs GPT-5.4 mini
GPT-5.4 mini is the stronger model overall, scoring 45.0 to 30.6 on the Noometry Index. Codestral costs 3.8× less per token, which makes it the better buy when GPT-5.4 mini's lead doesn't matter for your workload.
Last verified . 2 shared benchmarks.
Mistral AISummary
- They share 2 benchmarks with published results for both. Codestral scores higher in 0 categories and GPT-5.4 mini in 2 categories; 2 gaps are clear of the uncertainty.
- The widest gap is in coding, where GPT-5.4 mini leads 45.2 to 27.3.
- The biggest single-benchmark swing is Kagi LLM Benchmark: 32.5% for Codestral and 37.9% for GPT-5.4 mini.
- Codestral is cheaper at $0.30 / $0.90 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 256K.
Side by side
| Codestral | GPT-5.4 mini | |
|---|---|---|
| Provider | Mistral AI | OpenAI |
| Noometry Index | 30.6 | 45.0 |
| Released | 2024-05-29 | 2026-03-17 |
| Weights | Proprietary | Proprietary |
| Context window | 256K | 400K |
| Max output | 8K | 128K |
| Input $ / M tokens | $0.30 | $0.75 |
| Output $ / M tokens | $0.90 | $4.50 |
| Results tracked | 7 | 46 |
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Category by category
Coding GPT-5.4 mini leads
Codestral: 27.3 (#321), GPT-5.4 mini: 45.2 (#72)
| Benchmark | Codestral | GPT-5.4 mini |
|---|---|---|
| ALE-Bench | 137.78 | 1,189 |
| FrontierCode | — | 27% |
| Aider Polyglot | 11.1% | — |
| LMArena WebDev | — | 1397 |
| SciCode | — | 49.9% |
| WeirdML | — | 60.3% |
| BigCodeBench Instruct | 41.8% | — |
| LMArena Coding | — | 1438 |
| BigCodeBench Complete | 52.5% | — |
| HumanEval+ | 73.8% | — |
| MBPP+ | 61.9% | — |
Agentic & Tool Use Not comparable
Codestral: —, GPT-5.4 mini: 29.9 (#81)
| Benchmark | Codestral | GPT-5.4 mini |
|---|---|---|
| DeepResearch Bench | — | 36.3% |
Reasoning GPT-5.4 mini leads
Codestral: 19.8 (#251), GPT-5.4 mini: 30.4 (#85)
| Benchmark | Codestral | GPT-5.4 mini |
|---|---|---|
| Kagi LLM Benchmark | 32.5% | 37.9% |
| ARC-AGI-2 | — | 18.9% |
| NYT Connections (extended) | — | 61.8% |
| ARC-AGI-1 | — | 63.7% |
| CritPt | — | 10% |
| Chess Puzzles | — | 24% |
| Thematic Generalization | — | 61.7% |
| LMArena Hard Prompts | — | 1424 |
| Mystery Game Puzzles | — | 11% |
| DTBench | — | 80% |
| LMCA | — | 40.8% |
| Epoch Capabilities Index | — | 148.84 |
| ForecastBench | — | 57 |
Math Not comparable
Codestral: —, GPT-5.4 mini: 45.5 (#75)
| Benchmark | Codestral | GPT-5.4 mini |
|---|---|---|
| FrontierMath (Tiers 1-3) | — | 51.2% |
| FrontierMath Tier 4 | — | 9.8% |
| OTIS Mock AIME 2024-2025 | — | 88.9% |
| ProofBench | — | 21% |
| LMArena Math | — | 1419 |
| FrontierMath (Feb 2025 set) | — | 28.3% |
| FrontierMath Tier 4 (v1) | — | 2.1% |
Knowledge Not comparable
Codestral: —, GPT-5.4 mini: 51.5 (#67)
| Benchmark | Codestral | GPT-5.4 mini |
|---|---|---|
| GPQA Diamond | — | 86.9% |
| SimpleQA Verified | — | 29.4% |
| Vectara Hallucination Rate | — | 5.5% |
| LMArena Expert | — | 1435 |
Multimodal Not comparable
Codestral: —, GPT-5.4 mini: 39.7 (#56)
| Benchmark | Codestral | GPT-5.4 mini |
|---|---|---|
| LMArena Vision | — | 1245 |
Multilingual Not comparable
Codestral: —, GPT-5.4 mini: 51.9 (#96)
| Benchmark | Codestral | GPT-5.4 mini |
|---|---|---|
| LMArena Non-English | — | 1405 |
| LMArena Chinese | — | 1446 |
| LMArena French | — | 1440 |
| LMArena German | — | 1409 |
| LMArena Japanese | — | 1374 |
| LMArena Korean | — | 1368 |
| LMArena Russian | — | 1417 |
| LMArena Spanish | — | 1405 |
Instruction Following Not comparable
Codestral: —, GPT-5.4 mini: 74.1 (#102)
| Benchmark | Codestral | GPT-5.4 mini |
|---|---|---|
| LMArena Instruction Following | — | 1405 |
Long Context Not comparable
Codestral: —, GPT-5.4 mini: 43.0 (#112)
| Benchmark | Codestral | GPT-5.4 mini |
|---|---|---|
| LMArena Longer Query | — | 1407 |
Writing & Preference Not comparable
Codestral: —, GPT-5.4 mini: 64.0 (#58)
| Benchmark | Codestral | GPT-5.4 mini |
|---|---|---|
| LMArena Text | — | 1412 |
| LMArena Creative Writing | — | 1370 |
| EQ-Bench Creative Writing | — | 1665 |
| LMArena Multi-Turn | — | 1429 |
Frequently asked questions
Is Codestral better than GPT-5.4 mini?
GPT-5.4 mini is the stronger model overall, scoring 45.0 to 30.6 on the Noometry Index. Codestral costs 3.8× 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, Codestral or GPT-5.4 mini?
Codestral is cheaper. It lists at $0.30 per million input tokens and $0.90 per million output tokens; GPT-5.4 mini lists at $0.75 and $4.50.
Is Codestral or GPT-5.4 mini better for coding?
GPT-5.4 mini scores higher on coding benchmarks: 45.2 versus 27.3 in the Noometry coding category.
Which has the bigger context window?
GPT-5.4 mini does, with 400K tokens against 256K.
How many benchmarks do Codestral and GPT-5.4 mini share?
2 benchmarks have published results for both models. Codestral has 7 scored results on Noometry and GPT-5.4 mini has 46.