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.
70B24B
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.
128k40k
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—
Cheapest outputLowest output rate across every provider on OpenRouter, the lab included. May come from a different provider than the cheapest input.
$0.32DeepInfra—
$36.00DeepInfra · turbo · fp8—
Overview
CompanyMetaMistral
Release dateDec 6 2024Jun 10 2025
AccessOpen WeightClosed
Model detailsView modelView model

Frequently asked questions

LLaMA 3.3 and Magistral Small don't publish scores on any of the same benchmarks, so there's no direct head-to-head comparison. LLaMA 3.3 shipped 186 days before Magistral Small, so benchmark comparisons should account for the intervening progress.

LLaMA 3.3 has 70B parameters, while Magistral Small has 24B. Context windows are 128k (LLaMA 3.3) vs 40k (Magistral Small). LLaMA 3.3 is open weight, while Magistral Small is closed.

Direct benchmark comparisons are unavailable — LLaMA 3.3 and Magistral Small don't publish scores on any of the same benchmarks.