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/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.
8k128k
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.
—$0.075DeepInfra
Cheapest outputLowest output rate across every provider on OpenRouter, the lab included. May come from a different provider than the cheapest input.
—$0.20DeepInfra
—$25.00DeepInfra · fp8
Overview
CompanyMetaMistral
Release dateApr 18 2024Jun 20 2025
AccessOpen WeightOpen Weight
Model detailsView modelView model

Frequently asked questions

LLaMA 3 (8B/70B) and Mistral Small 3.2 don't publish scores on any of the same benchmarks, so there's no direct head-to-head comparison. LLaMA 3 (8B/70B) shipped 428 days before Mistral Small 3.2, so benchmark comparisons should account for the intervening progress.

LLaMA 3 (8B/70B) has 8B/70B parameters, while Mistral Small 3.2 has 24B. Context windows are 8k (LLaMA 3 (8B/70B)) vs 128k (Mistral Small 3.2).

Direct benchmark comparisons are unavailable — LLaMA 3 (8B/70B) and Mistral Small 3.2 don't publish scores on any of the same benchmarks.