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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.
7B24B
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.
4k32k
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.
—$0.05DeepInfra
Cheapest outputLowest output rate across every provider on OpenRouter, the lab included. May come from a different provider than the cheapest input.
—$0.08DeepInfra
—$14.00DeepInfra · fp8
Overview
CompanyDeepSeekMistral
Release dateFeb 5 2024Jan 30 2025
AccessOpen WeightOpen Weight
Model detailsView modelView model

Other comparisons

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

Frequently asked questions

DeepSeek-Math and Mistral Small 3 don't publish scores on any of the same benchmarks, so there's no direct head-to-head comparison. DeepSeek-Math shipped 360 days before Mistral Small 3, so benchmark comparisons should account for the intervening progress.

DeepSeek-Math has 7B parameters, while Mistral Small 3 has 24B. Context windows are 4k (DeepSeek-Math) vs 32k (Mistral Small 3).

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