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.
236B400B
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.
128k1M
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 dateMay 6 2024Apr 5 2025
AccessOpen WeightOpen Weight
Model detailsView modelView model

Frequently asked questions

DeepSeek V2 and LLaMA 4 Maverick don't publish scores on any of the same benchmarks, so there's no direct head-to-head comparison. DeepSeek V2 shipped 334 days before LLaMA 4 Maverick, so benchmark comparisons should account for the intervening progress.

DeepSeek V2 has 236B parameters, while LLaMA 4 Maverick has 400B. Context windows are 128k (DeepSeek V2) vs 1M (LLaMA 4 Maverick).

Direct benchmark comparisons are unavailable — DeepSeek V2 and LLaMA 4 Maverick don't publish scores on any of the same benchmarks.