AI Model Release Tracker

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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.
200k128k
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.
$1.10OpenAI$0.36DeepInfra
Cheapest outputLowest output rate across every provider on OpenRouter, the lab included. May come from a different provider than the cheapest input.
$4.40OpenAI$0.40DeepInfra
$440OpenAI$92.00DeepInfra · fp8
Overview
CompanyOpenAIQwen
Release dateApr 16 2025Sep 19 2024
AccessClosedOpen Weight
Model detailsView modelView model

Other comparisons

o4-mini-highvsClaude Haiku 5.5Qwen2.5vsClaude Haiku 5.5o4-mini-highvsGemini 4 ArgonQwen2.5vsGemini 4 Argono4-mini-highvsMuse Spark OpenQwen2.5vsMuse Spark Openo4-mini-highvsGrok 4.7Qwen2.5vsGrok 4.7o4-mini-highvsDeepSeek-V4.1-Flash-1017Qwen2.5vsDeepSeek-V4.1-Flash-1017o4-mini-highvsMistral Large 4Qwen2.5vsMistral Large 4

Frequently asked questions

o4-mini-high 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 209 days before o4-mini-high, so benchmark comparisons should account for the intervening progress.

Context windows are 200k (o4-mini-high) vs 128k (Qwen2.5). o4-mini-high is closed, while Qwen2.5 is open weight.

Direct benchmark comparisons are unavailable — o4-mini-high and Qwen2.5 don't publish scores on any of the same benchmarks.