Compare AI models
| Specifications | ||
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. | — | 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. | $1.25 | $10.00 |
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. | $10.00 | $30.00 |
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. | $0.125 | — |
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. | $0.625Google AI Studio | $10.00OpenAI |
Cheapest outputLowest output rate across third-party providers, excluding the lab itself. May come from a different provider than the cheapest input. | $5.00Google AI Studio | $30.00OpenAI |
| Benchmarks | ||
GPQA DiamondScience — Graduate-level science questions in biology, physics, and chemistry — hard enough that subject-matter PhDs score around 65%. Higher is better. | 86.4% | 42.5% |
BullshitBench v2Nonsense detection — Given a confidently-worded but nonsensical prompt, does the AI spot that it makes no sense and push back — instead of playing along and inventing an answer? The score is how often it clearly called out the nonsense. Higher is better. | 20% | — |
SWE-Bench VerifiedCoding — Real coding tasks pulled from open-source projects — the AI has to find and fix actual bugs. A human-checked version of the original SWE-Bench. Higher is better. | 59.6% | — |
Humanity's Last Exam · with toolsMultidisciplinary reasoning — Humanity's Last Exam — extremely hard expert questions across many subjects. “With tools” means the AI is allowed to search the web or run code while answering. Higher is better. | 18.8% | — |
MMMUMultimodal — Tests the AI on understanding images and text together across many college subjects. Higher is better. | 68% | — |
| Overview | ||
| Company | OpenAI | |
| Release date | Mar 25 2025 | Nov 6 2023 |
| Access | Closed | Closed |
| Model details | View model | View model |
Other comparisons
Gemini 2.5 ProvsClaude Haiku 5.5GPT-4 TurbovsClaude Haiku 5.5Gemini 2.5 ProvsMuse Spark 1.3GPT-4 TurbovsMuse Spark 1.3Gemini 2.5 ProvsGrok 4.7GPT-4 TurbovsGrok 4.7Gemini 2.5 ProvsDeepSeek-V4.1-FlashGPT-4 TurbovsDeepSeek-V4.1-FlashGemini 2.5 ProvsMistral Large 4GPT-4 TurbovsMistral Large 4Gemini 2.5 ProvsKimi K3GPT-4 TurbovsKimi K3Frequently asked questions
Gemini 2.5 Pro leads GPT-4 Turbo on 1 of the 1 benchmark they both report (GPQA Diamond). Gemini 2.5 Pro is cheaper on both input and output: $1.25 vs $10.00 per million input tokens, and $10.00 vs $30.00 per million output tokens. Figures are base-tier rates. GPT-4 Turbo shipped 505 days before Gemini 2.5 Pro, so benchmark comparisons should account for the intervening progress.
Published specifications for these two models are limited — see each model page for the latest details.
On GPQA Diamond, Gemini 2.5 Pro leads at 86.4% vs GPT-4 Turbo at 42.5%.