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/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.
1M128k
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
Cheapest outputLowest output rate across every provider on OpenRouter, the lab included. May come from a different provider than the cheapest input.
—$0.40DeepInfra
—$92.00DeepInfra · fp8
Overview
CompanyGoogleQwen
Release dateFeb 5 2025Sep 19 2024
AccessClosedOpen Weight
Model detailsView modelView model

Frequently asked questions

Gemini 2.0 Flash-Lite and Qwen2.5 don't publish scores on any of the same benchmarks, so there's no direct head-to-head comparison. Qwen2.5 shipped 139 days before Gemini 2.0 Flash-Lite, so benchmark comparisons should account for the intervening progress.

Context windows are 1M (Gemini 2.0 Flash-Lite) vs 128k (Qwen2.5). Gemini 2.0 Flash-Lite is closed, while Qwen2.5 is open weight.

Direct benchmark comparisons are unavailable — Gemini 2.0 Flash-Lite and Qwen2.5 don't publish scores on any of the same benchmarks.