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. | 1B/3B/11B/90B | 7B |
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. | 128k | 8k |
| API pricingUSD per 1M tokens · lower wins | ||
Cheapest inputLowest input rate across every provider on OpenRouter, the lab included. The cheapest endpoint may run a quantised build or a shorter context — see "Available from" on the model page. | $0.027Cloudflare | — |
Cheapest outputLowest output rate across every provider on OpenRouter, the lab included. May come from a different provider than the cheapest input. | $0.201Cloudflare | — |
| $15.45Cloudflare | — | |
| Overview | ||
| Company | Meta | Mistral |
| Release date | Sep 25 2024 | Sep 27 2023 |
| Access | Open Weight | Open Weight |
| Model details | View model | View model |
Other comparisons
LLaMA 3.2vsClaude Haiku 5.5Mistral 7BvsClaude Haiku 5.5LLaMA 3.2vsGPT-6.1 SolMistral 7BvsGPT-6.1 SolLLaMA 3.2vsGemini 4 ArgonMistral 7BvsGemini 4 ArgonLLaMA 3.2vsGrok 4.7Mistral 7BvsGrok 4.7LLaMA 3.2vsDeepSeek-V4.1-Flash-1017Mistral 7BvsDeepSeek-V4.1-Flash-1017LLaMA 3.2vsKimi K3Mistral 7BvsKimi K3Frequently asked questions
LLaMA 3.2 and Mistral 7B don't publish scores on any of the same benchmarks, so there's no direct head-to-head comparison. Mistral 7B shipped 364 days before LLaMA 3.2, so benchmark comparisons should account for the intervening progress.
LLaMA 3.2 has 1B/3B/11B/90B parameters, while Mistral 7B has 7B. Context windows are 128k (LLaMA 3.2) vs 8k (Mistral 7B).
Direct benchmark comparisons are unavailable — LLaMA 3.2 and Mistral 7B don't publish scores on any of the same benchmarks.