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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.
4k128k
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
CompanyDeepSeekMistral
Release dateFeb 5 2024May 7 2025
AccessOpen WeightClosed
Model detailsView modelView model

Other comparisons

DeepSeek-MathvsClaude Haiku 5.5Mistral Medium 3vsClaude Haiku 5.5DeepSeek-MathvsGPT-6.1 SolMistral Medium 3vsGPT-6.1 SolDeepSeek-MathvsGemini 4 ArgonMistral Medium 3vsGemini 4 ArgonDeepSeek-MathvsMuse Spark OpenMistral Medium 3vsMuse Spark OpenDeepSeek-MathvsGrok 4.7Mistral Medium 3vsGrok 4.7DeepSeek-MathvsKimi K3Mistral Medium 3vsKimi K3

Frequently asked questions

DeepSeek-Math and Mistral Medium 3 don't publish scores on any of the same benchmarks, so there's no direct head-to-head comparison. DeepSeek-Math shipped 457 days before Mistral Medium 3, so benchmark comparisons should account for the intervening progress.

Context windows are 4k (DeepSeek-Math) vs 128k (Mistral Medium 3). DeepSeek-Math is open weight, while Mistral Medium 3 is closed.

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