Gemini 2.5 Pro vs o3
Gemini 2.5 Pro
| Gemini 2.5 Pro | o3 | |
|---|---|---|
| Provider | OpenAI | |
| Context window Maximum tokens (input + output) the model can process in a single request. Glossary β | 1,048,576 | 200,000 |
| Capabilities Optional capabilities the model advertises: vision (images), tools (function calling), json_mode (structured output). | vision, tools, json_mode | vision, tools, json_mode |
| Input $ / 1M tokens Cost for tokens you send (prompt + context). Cheaper side highlighted. Glossary β | 1.2500 | 2.0000 |
| Output $ / 1M tokens Cost for tokens the model generates. Output is normally 3β5Γ pricier than input. Glossary β | 10.0000 | 8.0000 |
Frequently asked questions
Which is cheaper, Gemini 2.5 Pro or o3?
o3 is cheaper than Gemini 2.5 Pro on a 50/50 input/output blend by about $0.625 per 1M tokens. Exact savings depend on your input-vs-output ratio β use the cost calculator on this page for a workload-specific estimate.
Which has a larger context window, Gemini 2.5 Pro or o3?
Gemini 2.5 Pro has the larger context window at 1M tokens versus 200k tokens for o3. That means Gemini 2.5 Pro can ingest about 5.2x as much text per request.
What is the difference between Gemini 2.5 Pro and o3?
Gemini 2.5 Pro comes from Google; o3 comes from OpenAI. They differ in pricing, context window, and supported capabilities β see the side-by-side table on this page for the exact figures, refreshed nightly.