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/3B/7B/14B/32B/72B480B
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.
—256k
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.
$0.36DeepInfra$0.30DeepInfra
Cheapest outputLowest output rate across every provider on OpenRouter, the lab included. May come from a different provider than the cheapest input.
$0.40DeepInfra$1.00DeepInfra
$92.00DeepInfra · fp8$110DeepInfra · turbo · fp4
These models have no shared benchmark scores.
Overview
CompanyQwenQwen
Release dateSep 19 2024Jul 22 2025
AccessOpen WeightOpen Weight
Model detailsView modelView model

Frequently asked questions

Qwen2.5 and Qwen3-Coder don't publish scores on any of the same benchmarks, so there's no direct head-to-head comparison. Qwen2.5 shipped 306 days before Qwen3-Coder, so benchmark comparisons should account for the intervening progress.

Qwen2.5 has 0.5B/1.5B/3B/7B/14B/32B/72B parameters, while Qwen3-Coder has 480B.

Direct benchmark comparisons are unavailable — Qwen2.5 and Qwen3-Coder don't publish scores on any of the same benchmarks.