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.
—480B
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.
256k256k
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.
—$0.30DeepInfra
Cheapest outputLowest output rate across every provider on OpenRouter, the lab included. May come from a different provider than the cheapest input.
—$1.00DeepInfra
—$110DeepInfra · turbo · fp4
These models have no shared benchmark scores.
Overview
CompanyMistralQwen
Release dateJan 13 2025Jul 22 2025
AccessClosedOpen Weight
Model detailsView modelView model

Frequently asked questions

Codestral 25.01 and Qwen3-Coder don't publish scores on any of the same benchmarks, so there's no direct head-to-head comparison. Codestral 25.01 shipped 190 days before Qwen3-Coder, so benchmark comparisons should account for the intervening progress.

Context windows are 256k (Codestral 25.01) vs 256k (Qwen3-Coder). Codestral 25.01 is closed, while Qwen3-Coder is open weight.

Direct benchmark comparisons are unavailable — Codestral 25.01 and Qwen3-Coder don't publish scores on any of the same benchmarks.