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.
109B12B
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.
10M128k
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.
$0.10DeepInfra$0.0166Io Net
Cheapest outputLowest output rate across every provider on OpenRouter, the lab included. May come from a different provider than the cheapest input.
$0.30DeepInfra$0.0216Io Net
$35.00DeepInfra · fp8$4.40Io Net · fp16
These models have no shared benchmark scores.
Overview
CompanyMetaMistral
Release dateApr 5 2025Jul 18 2024
AccessOpen WeightOpen Weight
Model detailsView modelView model

Frequently asked questions

LLaMA 4 Scout and Mistral NeMo don't publish scores on any of the same benchmarks, so there's no direct head-to-head comparison. Mistral NeMo shipped 261 days before LLaMA 4 Scout, so benchmark comparisons should account for the intervening progress.

LLaMA 4 Scout has 109B parameters, while Mistral NeMo has 12B. Context windows are 10M (LLaMA 4 Scout) vs 128k (Mistral NeMo).

Direct benchmark comparisons are unavailable — LLaMA 4 Scout and Mistral NeMo don't publish scores on any of the same benchmarks.