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. | — | 0.5B/1.5B/7B/57B/72B |
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 | 128k |
| Overview | ||
| Company | Mistral | Qwen |
| Release date | Dec 11 2023 | Jun 6 2024 |
| Access | Closed | Open Weight |
| Model details | View model | View model |
Other comparisons
Mistral MediumvsClaude Haiku 5.5Qwen2vsClaude Haiku 5.5Mistral MediumvsGPT-6.1 SolQwen2vsGPT-6.1 SolMistral MediumvsGemini 4 ArgonQwen2vsGemini 4 ArgonMistral MediumvsMuse Spark OpenQwen2vsMuse Spark OpenMistral MediumvsGrok 4.7Qwen2vsGrok 4.7Mistral MediumvsDeepSeek-V4.1-Flash-1017Qwen2vsDeepSeek-V4.1-Flash-1017Frequently asked questions
Mistral Medium and Qwen2 don't publish scores on any of the same benchmarks, so there's no direct head-to-head comparison. Mistral Medium shipped 178 days before Qwen2, so benchmark comparisons should account for the intervening progress.
Context windows are 32k (Mistral Medium) vs 128k (Qwen2). Mistral Medium is closed, while Qwen2 is open weight.
Direct benchmark comparisons are unavailable — Mistral Medium and Qwen2 don't publish scores on any of the same benchmarks.