AI Model Release Tracker

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.
16B123B
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.
—$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 dateJan 11 2024Jul 24 2024
AccessOpen WeightOpen Weight
Model detailsView modelView model

Other comparisons

DeepSeek-MoEvsClaude Haiku 5.5Mistral Large 2vsClaude Haiku 5.5DeepSeek-MoEvsGPT-6.1 SolMistral Large 2vsGPT-6.1 SolDeepSeek-MoEvsGemini 4 ArgonMistral Large 2vsGemini 4 ArgonDeepSeek-MoEvsMuse Spark OpenMistral Large 2vsMuse Spark OpenDeepSeek-MoEvsGrok 4.7Mistral Large 2vsGrok 4.7DeepSeek-MoEvsKimi K3Mistral Large 2vsKimi K3

Frequently asked questions

DeepSeek-MoE and Mistral Large 2 don't publish scores on any of the same benchmarks, so there's no direct head-to-head comparison. DeepSeek-MoE shipped 195 days before Mistral Large 2, so benchmark comparisons should account for the intervening progress.

DeepSeek-MoE has 16B parameters, while Mistral Large 2 has 123B. Context windows are 4k (DeepSeek-MoE) vs 128k (Mistral Large 2).

Direct benchmark comparisons are unavailable — DeepSeek-MoE and Mistral Large 2 don't publish scores on any of the same benchmarks.