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.
—123B
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.
200k256k
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
Benchmarks
SWE-Bench VerifiedCoding — Real coding tasks pulled from open-source projects — the AI has to find and fix actual bugs. A human-checked version of the original SWE-Bench. Higher is better.
49%72.2%
Overview
CompanyAnthropicMistral
Release dateOct 22 2024Dec 9 2025
AccessClosedOpen Weight
Model detailsView modelView model

Frequently asked questions

Devstral 2 (123B) leads Claude 3.5 Sonnet (upgraded) on 1 of the 1 benchmark they both report (SWE-Bench Verified). Claude 3.5 Sonnet (upgraded) shipped 413 days before Devstral 2 (123B), so benchmark comparisons should account for the intervening progress.

Context windows are 200k (Claude 3.5 Sonnet (upgraded)) vs 256k (Devstral 2 (123B)). Claude 3.5 Sonnet (upgraded) is closed, while Devstral 2 (123B) is open weight.

On SWE-Bench Verified, Devstral 2 (123B) leads at 72.2% vs Claude 3.5 Sonnet (upgraded) at 49%.