AI Model Release Tracker

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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.
16B/236B—
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.
128k32k
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
CompanyDeepSeekMistral
Release dateJun 17 2024Feb 26 2024
AccessOpen WeightClosed
Model detailsView modelView model

Other comparisons

DeepSeek Coder V2vsClaude Haiku 5.5Mistral LargevsClaude Haiku 5.5DeepSeek Coder V2vsGPT-6.1 SolMistral LargevsGPT-6.1 SolDeepSeek Coder V2vsGemini 4 ArgonMistral LargevsGemini 4 ArgonDeepSeek Coder V2vsMuse Spark OpenMistral LargevsMuse Spark OpenDeepSeek Coder V2vsGrok 4.7Mistral LargevsGrok 4.7DeepSeek Coder V2vsKimi K3Mistral LargevsKimi K3

Frequently asked questions

DeepSeek Coder V2 and Mistral Large don't publish scores on any of the same benchmarks, so there's no direct head-to-head comparison. Mistral Large shipped 112 days before DeepSeek Coder V2, so benchmark comparisons should account for the intervening progress.

Context windows are 128k (DeepSeek Coder V2) vs 32k (Mistral Large). DeepSeek Coder V2 is open weight, while Mistral Large is closed.

Direct benchmark comparisons are unavailable — DeepSeek Coder V2 and Mistral Large don't publish scores on any of the same benchmarks.