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 |
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. | 32k | 2k |
| 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. | $2.00Mistral | — |
Cheapest outputLowest output rate across every provider on OpenRouter, the lab included. May come from a different provider than the cheapest input. | $6.00Mistral | — |
| $700Mistral | — | |
| Overview | ||
| Company | Mistral | Qwen |
| Release date | Feb 26 2024 | Aug 3 2023 |
| Access | Closed | Open Weight |
| Model details | View model | View model |
Other comparisons
Mistral LargevsClaude Haiku 5.5Qwen-7BvsClaude Haiku 5.5Mistral LargevsGPT-6.1 SolQwen-7BvsGPT-6.1 SolMistral LargevsGemini 4 ArgonQwen-7BvsGemini 4 ArgonMistral LargevsMuse Spark OpenQwen-7BvsMuse Spark OpenMistral LargevsGrok 4.7Qwen-7BvsGrok 4.7Mistral LargevsDeepSeek-V4.1-Flash-1017Qwen-7BvsDeepSeek-V4.1-Flash-1017Frequently asked questions
Mistral Large and Qwen-7B don't publish scores on any of the same benchmarks, so there's no direct head-to-head comparison. Qwen-7B shipped 207 days before Mistral Large, so benchmark comparisons should account for the intervening progress.
Context windows are 32k (Mistral Large) vs 2k (Qwen-7B). Mistral Large is closed, while Qwen-7B is open weight.
Direct benchmark comparisons are unavailable — Mistral Large and Qwen-7B don't publish scores on any of the same benchmarks.