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. | 7B/13B/34B | — |
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 | 32k |
| Overview | ||
| Company | Meta | Mistral |
| Release date | Aug 24 2023 | Feb 26 2024 |
| Access | Open Weight | Closed |
| Model details | View model | View model |
Other comparisons
Code LlamavsClaude Haiku 5.5Mistral SmallvsClaude Haiku 5.5Code LlamavsGPT-6.1 SolMistral SmallvsGPT-6.1 SolCode LlamavsGemini 4 ArgonMistral SmallvsGemini 4 ArgonCode LlamavsGrok 4.7Mistral SmallvsGrok 4.7Code LlamavsDeepSeek-V4.1-Flash-1017Mistral SmallvsDeepSeek-V4.1-Flash-1017Code LlamavsKimi K3Mistral SmallvsKimi K3Frequently asked questions
Code Llama and Mistral Small don't publish scores on any of the same benchmarks, so there's no direct head-to-head comparison. Code Llama shipped 186 days before Mistral Small, so benchmark comparisons should account for the intervening progress.
Context windows are 16k (Code Llama) vs 32k (Mistral Small). Code Llama is open weight, while Mistral Small is closed.
Direct benchmark comparisons are unavailable — Code Llama and Mistral Small don't publish scores on any of the same benchmarks.