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.
7B12B
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.
—$0.0166Io Net
Cheapest outputLowest output rate across every provider on OpenRouter, the lab included. May come from a different provider than the cheapest input.
—$0.0216Io Net
—$4.40Io Net · fp16
Overview
CompanyDeepSeekMistral
Release dateFeb 5 2024Jul 18 2024
AccessOpen WeightOpen Weight
Model detailsView modelView model

Other comparisons

DeepSeek-MathvsClaude Haiku 5.5Mistral NeMovsClaude Haiku 5.5DeepSeek-MathvsGPT-6.1 SolMistral NeMovsGPT-6.1 SolDeepSeek-MathvsGemini 4 ArgonMistral NeMovsGemini 4 ArgonDeepSeek-MathvsMuse Spark OpenMistral NeMovsMuse Spark OpenDeepSeek-MathvsGrok 4.7Mistral NeMovsGrok 4.7DeepSeek-MathvsKimi K3Mistral NeMovsKimi K3

Frequently asked questions

DeepSeek-Math and Mistral NeMo don't publish scores on any of the same benchmarks, so there's no direct head-to-head comparison. DeepSeek-Math shipped 164 days before Mistral NeMo, so benchmark comparisons should account for the intervening progress.

DeepSeek-Math has 7B parameters, while Mistral NeMo has 12B. Context windows are 4k (DeepSeek-Math) vs 128k (Mistral NeMo).

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