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—
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.
32k400k
API pricingUSD per 1M tokens · lower wins
Input priceWhat you pay for everything you send the model — your question, plus any documents or earlier conversation you include with it.
—$1.25
Output priceWhat you pay for the text the model writes back. It is normally the dearer half: producing an answer costs more than reading one.
—$10.00
Cached input priceA reduced rate for text you send over and over. If every request starts with the same instructions or the same document, the provider keeps a copy ready and charges less to read it again.
—$0.125
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.
—$1.25Azure
Cheapest outputLowest output rate across every provider on OpenRouter, the lab included. May come from a different provider than the cheapest input.
—$10.00Azure
—$750OpenAI list price
These models have no shared benchmark scores.
Overview
CompanyMistralOpenAI
Release dateJul 16 2024Aug 7 2025
AccessOpen WeightClosed
Model detailsView modelView model

Frequently asked questions

Mathstral 7B and GPT-5 don't publish scores on any of the same benchmarks, so there's no direct head-to-head comparison. Only GPT-5 has a verified first-party API price: $1.25 per million input tokens and $10.00 per million output tokens. No pay-as-you-go API rate is tracked for Mathstral 7B. Mathstral 7B shipped 387 days before GPT-5, so benchmark comparisons should account for the intervening progress.

Context windows are 32k (Mathstral 7B) vs 400k (GPT-5). Mathstral 7B is open weight, while GPT-5 is closed.

Direct benchmark comparisons are unavailable — Mathstral 7B and GPT-5 don't publish scores on any of the same benchmarks.