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.
—8B/49B
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.
32k128k
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.
$2.00Mistral—
Cheapest outputLowest output rate across every provider on OpenRouter, the lab included. May come from a different provider than the cheapest input.
$6.00Mistral—
$700Mistral—
Overview
CompanyMistralNVIDIA
Release dateFeb 26 2024Mar 18 2025
AccessClosedOpen Weight
Model detailsView modelView model

Frequently asked questions

Mistral Large and Llama Nemotron (Nano/Super) don't publish scores on any of the same benchmarks, so there's no direct head-to-head comparison. Mistral Large shipped 386 days before Llama Nemotron (Nano/Super), so benchmark comparisons should account for the intervening progress.

Context windows are 32k (Mistral Large) vs 128k (Llama Nemotron (Nano/Super)). Mistral Large is closed, while Llama Nemotron (Nano/Super) is open weight.

Direct benchmark comparisons are unavailable — Mistral Large and Llama Nemotron (Nano/Super) don't publish scores on any of the same benchmarks.