o1vsQwQ-32B
o1 | QwQ-32B | |
|---|---|---|
| Specifications | ||
ParametersA rough measure of how big the model is. More parameters usually means more capable and more expensive to run, though it is a poor guide on its own — a smaller, newer model often beats a larger, older one. | — | 32B |
Context windowHow much text the model can hold in mind at once — your question, any documents you attach, the conversation so far, and its own reply. Go past it and the earliest part falls out of view. | 200k | 128k |
| 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. | $60.00 | — |
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. | $7.50 | — |
| BenchmarksPublished by one model only | ||
GPQA DiamondScience — Graduate-level science questions in biology, physics, and chemistry — hard enough that subject-matter PhDs score around 65%. Higher is better. | 75.7% | — |
| Overview | ||
| Company | OpenAI | Qwen |
| Release date | Dec 5 2024 | Mar 6 2025 |
| Access | Proprietary | Open Weight |
Other comparisons
Frequently asked questions
o1 and QwQ-32B don't publish scores on any of the same benchmarks, so there's no direct head-to-head comparison. Only o1 has a verified first-party API price: $15.00 per million input tokens and $60.00 per million output tokens. No pay-as-you-go API rate is tracked for QwQ-32B. o1 shipped 91 days before QwQ-32B, so benchmark comparisons should account for the intervening progress.
Context windows are 200k (o1) vs 128k (QwQ-32B). o1 is proprietary, while QwQ-32B is open weight.
Direct benchmark comparisons are unavailable — o1 and QwQ-32B don't publish scores on any of the same benchmarks.