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.
—0.5B/1.5B/7B/57B/72B
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.
400k128k
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.
$15.00—
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.
$120.00—
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.
$15.00OpenAI—
Cheapest outputLowest output rate across every provider on OpenRouter, the lab included. May come from a different provider than the cheapest input.
$120.00OpenAI—
$9,000OpenAI list price—
Overview
CompanyOpenAIQwen
Release dateAug 7 2025Jun 6 2024
AccessClosedOpen Weight
Model detailsView modelView model

Frequently asked questions

GPT-5 Pro and Qwen2 don't publish scores on any of the same benchmarks, so there's no direct head-to-head comparison. Only GPT-5 Pro has a verified first-party API price: $15.00 per million input tokens and $120.00 per million output tokens. No pay-as-you-go API rate is tracked for Qwen2. Qwen2 shipped 427 days before GPT-5 Pro, so benchmark comparisons should account for the intervening progress.

Context windows are 400k (GPT-5 Pro) vs 128k (Qwen2). GPT-5 Pro is closed, while Qwen2 is open weight.

Direct benchmark comparisons are unavailable — GPT-5 Pro and Qwen2 don't publish scores on any of the same benchmarks.