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.
—400B
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.
2M1M
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
CompanyGoogleMeta
Release dateSep 24 2024Apr 5 2025
AccessClosedOpen Weight
Model detailsView modelView model

Frequently asked questions

Gemini 1.5 Pro-002 and LLaMA 4 Maverick don't publish scores on any of the same benchmarks, so there's no direct head-to-head comparison. Gemini 1.5 Pro-002 shipped 193 days before LLaMA 4 Maverick, so benchmark comparisons should account for the intervening progress.

Context windows are 2M (Gemini 1.5 Pro-002) vs 1M (LLaMA 4 Maverick). Gemini 1.5 Pro-002 is closed, while LLaMA 4 Maverick is open weight.

Direct benchmark comparisons are unavailable — Gemini 1.5 Pro-002 and LLaMA 4 Maverick don't publish scores on any of the same benchmarks.