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.
119B8B/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.
256k128k
API pricingUSD per 1M tokens · lower wins
Input priceWhat you pay for everything you send the model — your question, plus any documents or earlier conversation you include with it.
$0.15—
Output priceWhat you pay for the text the model writes back. It is normally the dearer half: producing an answer costs more than reading one.
$0.60—
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.
$0.15Mistral—
Cheapest outputLowest output rate across every provider on OpenRouter, the lab included. May come from a different provider than the cheapest input.
$0.60Mistral—
$60.00Mistral list price—
These models have no shared benchmark scores.
Overview
CompanyMistralNVIDIA
Release dateMar 16 2026Mar 18 2025
AccessClosedOpen Weight
Model detailsView modelView model

Frequently asked questions

Mistral Small 4 and Llama Nemotron (Nano/Super) don't publish scores on any of the same benchmarks, so there's no direct head-to-head comparison. Only Mistral Small 4 has a verified first-party API price: $0.15 per million input tokens and $0.60 per million output tokens. No pay-as-you-go API rate is tracked for Llama Nemotron (Nano/Super). Llama Nemotron (Nano/Super) shipped 363 days before Mistral Small 4, so benchmark comparisons should account for the intervening progress.

Mistral Small 4 has 119B parameters, while Llama Nemotron (Nano/Super) has 8B/49B. Context windows are 256k (Mistral Small 4) vs 128k (Llama Nemotron (Nano/Super)). Mistral Small 4 is closed, while Llama Nemotron (Nano/Super) is open weight.

Direct benchmark comparisons are unavailable — Mistral Small 4 and Llama Nemotron (Nano/Super) don't publish scores on any of the same benchmarks.