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.
400B253B
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.
1M128k
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
CompanyMetaNVIDIA
Release dateApr 5 2025Apr 8 2025
AccessOpen WeightOpen Weight
Model detailsView modelView model

Frequently asked questions

LLaMA 4 Maverick and Llama Nemotron Ultra 253B don't publish scores on any of the same benchmarks, so there's no direct head-to-head comparison. LLaMA 4 Maverick shipped 3 days before Llama Nemotron Ultra 253B, so benchmark comparisons should account for the intervening progress.

LLaMA 4 Maverick has 400B parameters, while Llama Nemotron Ultra 253B has 253B. Context windows are 1M (LLaMA 4 Maverick) vs 128k (Llama Nemotron Ultra 253B).

Direct benchmark comparisons are unavailable — LLaMA 4 Maverick and Llama Nemotron Ultra 253B don't publish scores on any of the same benchmarks.