Models · Compare
Codestral 22B v0.1 vs GPT-4o
Rows highlighted in warm gray are where the models differ. Numbers carry their as-of date and primary source.
Specs
| Field | A: Codestral 22B v0.1 | B: GPT-4o |
|---|---|---|
| Released | 2024-05-29 | 2024-05-13 |
| Developer | Mistral AI | OpenAI |
| Openness | Source-available | Proprietary |
| License | Mistral AI Non-Production License (MNPL-0.1) | Proprietary |
| OSI-approved | no | no |
| Data released | no | no |
| Training code | no | no |
| Architecture | dense | unknown |
| Total params | 22B | — |
| Active params | — | — |
| Experts | — | — |
| Context window | 33K | — |
| Attention | gqa | unknown |
| Position enc. | rope | unknown |
| Pretraining tokens | — | — |
| Post-training | sft | rlhf |
| Training hardware | — | — |
| $/M input | — | $2.50 |
| $/M output | — | $10.00 |
| Output tok/sec | — | 131.6 |
Benchmarks
Missing scores render as not reported; never inferred. Bold highlights the leader per benchmark.
General reasoning
| MMLU-Pro | — | 74.8 2026-05-21 |
| GPQA-Diamond | — | 54.3 2026-05-21 |
Code
| LiveCodeBench | — | 30.9 2026-05-21 |
Math
| MATH | — | 75.9 2026-05-21 |
| AIME 2024 | — | 15.0 2026-05-21 |
| AIME 2025 | — | 6.0 2026-05-21 |
Context · A
Mistral's first code-specialist release, weights-available in May 2024 under the Mistral AI Non-Production License (research and testing only, commercial requires a separate license). Trained on 80+ programming languages with a 32K context, four to eight times longer than contemporary code models, and supports both instruct-style answering and fill-in-the-middle completion for IDE integrations.
Context · B
Native-multimodal model with audio + vision + text in a single pretrained backbone. Pushed real-time voice latency to under 400ms; the multimodal benchmark anchor through 2024.