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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.
128k2k
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.
$0.40Mistral—
Cheapest outputLowest output rate across every provider on OpenRouter, the lab included. May come from a different provider than the cheapest input.
$2.00Mistral—
$180Mistral · zdr—
Overview
CompanyMistralQwen
Release dateMay 7 2025Aug 3 2023
AccessClosedOpen Weight
Model detailsView modelView model

Other comparisons

Mistral Medium 3vsClaude Haiku 5.5Qwen-7BvsClaude Haiku 5.5Mistral Medium 3vsGPT-6.1 SolQwen-7BvsGPT-6.1 SolMistral Medium 3vsGemini 4 ArgonQwen-7BvsGemini 4 ArgonMistral Medium 3vsMuse Spark OpenQwen-7BvsMuse Spark OpenMistral Medium 3vsGrok 4.7Qwen-7BvsGrok 4.7Mistral Medium 3vsDeepSeek-V4.1-Flash-1017Qwen-7BvsDeepSeek-V4.1-Flash-1017

Frequently asked questions

Mistral Medium 3 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 643 days before Mistral Medium 3, so benchmark comparisons should account for the intervening progress.

Context windows are 128k (Mistral Medium 3) vs 2k (Qwen-7B). Mistral Medium 3 is closed, while Qwen-7B is open weight.

Direct benchmark comparisons are unavailable — Mistral Medium 3 and Qwen-7B don't publish scores on any of the same benchmarks.