Compare AI models
| Specifications | ||
ParametersThe learned values that shape how a model responds. B means billion and T means trillion. For mixture-of-experts models, the total count is larger than the number active for each token. Parameter count alone does not measure quality. | 70B | 24B |
Context windowHow much information the model can work with in one request, measured in tokens — pieces of words or other data. This includes your question, attachments, conversation and reply. Limits can vary by model variant and provider. | 16k | 128k |
| These models have no shared benchmark scores. | ||
SWE-Bench VerifiedCoding — Real coding tasks pulled from open-source projects — the AI has to find and fix actual bugs. A human-checked version of the original SWE-Bench. Higher is better. | — | 46.8% |
| Overview | ||
| Company | Meta | Mistral |
| Release date | Jan 29 2024 | May 21 2025 |
| Access | Open Weight | Open Weight |
| Model details | View model | View model |
Other comparisons
Code Llama 70BvsClaude Haiku 5.5Devstral SmallvsClaude Haiku 5.5Code Llama 70BvsGPT-6.1 SolDevstral SmallvsGPT-6.1 SolCode Llama 70BvsGemini 4 ArgonDevstral SmallvsGemini 4 ArgonCode Llama 70BvsGrok 4.7Devstral SmallvsGrok 4.7Code Llama 70BvsDeepSeek-V4.1-Flash-1017Devstral SmallvsDeepSeek-V4.1-Flash-1017Code Llama 70BvsKimi K3Devstral SmallvsKimi K3Frequently asked questions
Code Llama 70B and Devstral Small don't publish scores on any of the same benchmarks, so there's no direct head-to-head comparison. Code Llama 70B shipped 478 days before Devstral Small, so benchmark comparisons should account for the intervening progress.
Code Llama 70B has 70B parameters, while Devstral Small has 24B. Context windows are 16k (Code Llama 70B) vs 128k (Devstral Small).
Direct benchmark comparisons are unavailable — Code Llama 70B and Devstral Small don't publish scores on any of the same benchmarks.