Compare AI models
| Specifications | ||
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. | 2M | 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 |
| — | $6,000OpenAI list price | |
| These models have no shared benchmark scores. | ||
GPQA DiamondScience — Graduate-level science questions in biology, physics, and chemistry — hard enough that subject-matter PhDs score around 65%. Higher is better. | — | 73.3% |
| Overview | ||
| Company | OpenAI | |
| Release date | Feb 5 2025 | Sep 12 2024 |
| Access | Closed | Closed |
| Model details | View model | View model |
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Gemini 2.0 Pro and o1-preview don't publish scores on any of the same benchmarks, so there's no direct head-to-head comparison. Only o1-preview 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 Gemini 2.0 Pro. o1-preview shipped 146 days before Gemini 2.0 Pro, so benchmark comparisons should account for the intervening progress.
Context windows are 2M (Gemini 2.0 Pro) vs 128k (o1-preview).
Direct benchmark comparisons are unavailable — Gemini 2.0 Pro and o1-preview don't publish scores on any of the same benchmarks.