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.
9B/27B400B
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.
8k1M
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.
$0.65NextBit$0.1875DigitalOcean
Cheapest outputLowest output rate across every provider on OpenRouter, the lab included. May come from a different provider than the cheapest input.
$0.65NextBit$0.6525DigitalOcean
$163NextBit · int4$70.13DigitalOcean
These models have no shared benchmark scores.
Overview
CompanyGoogleMeta
Release dateJun 27 2024Apr 5 2025
AccessOpen WeightOpen Weight
Model detailsView modelView model

Frequently asked questions

Gemma 2 and LLaMA 4 Maverick don't publish scores on any of the same benchmarks, so there's no direct head-to-head comparison. Gemma 2 shipped 282 days before LLaMA 4 Maverick, so benchmark comparisons should account for the intervening progress.

Gemma 2 has 9B/27B parameters, while LLaMA 4 Maverick has 400B. Context windows are 8k (Gemma 2) vs 1M (LLaMA 4 Maverick).

Direct benchmark comparisons are unavailable — Gemma 2 and LLaMA 4 Maverick don't publish scores on any of the same benchmarks.