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.
7B400B
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.
4k1M
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.
—$0.1875DigitalOcean
Cheapest outputLowest output rate across every provider on OpenRouter, the lab included. May come from a different provider than the cheapest input.
—$0.6525DigitalOcean
—$70.13DigitalOcean
These models have no shared benchmark scores.
Overview
CompanyDeepSeekMeta
Release dateFeb 5 2024Apr 5 2025
AccessOpen WeightOpen Weight
Model detailsView modelView model

Frequently asked questions

DeepSeek-Math and LLaMA 4 Maverick don't publish scores on any of the same benchmarks, so there's no direct head-to-head comparison. DeepSeek-Math shipped 425 days before LLaMA 4 Maverick, so benchmark comparisons should account for the intervening progress.

DeepSeek-Math has 7B parameters, while LLaMA 4 Maverick has 400B. Context windows are 4k (DeepSeek-Math) vs 1M (LLaMA 4 Maverick).

Direct benchmark comparisons are unavailable — DeepSeek-Math and LLaMA 4 Maverick don't publish scores on any of the same benchmarks.