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.
7B/13B/34B123B
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.
16k256k
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.
—$0.40Mistral
Cheapest outputLowest output rate across every provider on OpenRouter, the lab included. May come from a different provider than the cheapest input.
—$2.00Mistral
—$180Mistral
These models have no shared benchmark scores.
Overview
CompanyMetaMistral
Release dateAug 24 2023Dec 9 2025
AccessOpen WeightOpen Weight
Model detailsView modelView model

Frequently asked questions

Code Llama and Devstral 2 (123B) don't publish scores on any of the same benchmarks, so there's no direct head-to-head comparison. Code Llama shipped 838 days before Devstral 2 (123B), so benchmark comparisons should account for the intervening progress.

Code Llama has 7B/13B/34B parameters, while Devstral 2 (123B) has 123B. Context windows are 16k (Code Llama) vs 256k (Devstral 2 (123B)).

Direct benchmark comparisons are unavailable — Code Llama and Devstral 2 (123B) don't publish scores on any of the same benchmarks.