o1vsQwen3
o1 | Qwen3 | |
|---|---|---|
| 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. | — | 235B |
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 · base tier | ||
Input priceWhat you pay for everything you send the model — your question, plus any documents or earlier conversation you include with it. | $15.00 | $0.70 |
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 | $2.80 |
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 | — |
Cheapest inputLowest input rate across third-party providers, excluding the lab itself. The cheapest endpoint may run a quantised build or a shorter context — see "Available from" on the model page. | — | $0.0482StreamLake |
Cheapest outputLowest output rate across third-party providers, excluding the lab itself. May come from a different provider than the cheapest input. | — | $0.1931StreamLake |
| 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 | Apr 29 2025 |
| Access | Proprietary | Open Weight |
Other comparisons
Frequently asked questions
o1 and Qwen3 don't publish scores on any of the same benchmarks, so there's no direct head-to-head comparison. Qwen3 is cheaper on both input and output: $0.70 vs $15.00 per million input tokens, and $2.80 vs $60.00 per million output tokens. Figures are base-tier rates. o1 shipped 145 days before Qwen3, so benchmark comparisons should account for the intervening progress.
Context windows are 200k (o1) vs 128k (Qwen3). o1 is proprietary, while Qwen3 is open weight.
Direct benchmark comparisons are unavailable — o1 and Qwen3 don't publish scores on any of the same benchmarks.