Side-by-side comparison
o3 vs Gemini 2.5 Pro
Google
Gemini 2.5 Pro
👁 Vision
🔧 Tools
{} JSON
Input / 1M
$1.2500
Output / 1M
$10.0000
| o3 | Gemini 2.5 Pro | |
|---|---|---|
| Provider | OpenAI | |
| Context window Maximum tokens (input + output) the model can process in a single request. Glossary → | 200,000 | 1,048,576 |
| 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 → | 2.0000 | 1.2500 |
| Output $ / 1M tokens Cost for tokens the model generates. Output is normally 3–5× pricier than input. Glossary → | 8.0000 | 10.0000 |
Frequently asked questions
Which is cheaper, o3 or Gemini 2.5 Pro?
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 — use the cost calculator on this page for a workload-specific estimate.
Which has a larger context window, o3 or Gemini 2.5 Pro?
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 o3 and Gemini 2.5 Pro?
o3 comes from OpenAI; Gemini 2.5 Pro comes from Google. They differ in pricing, context window, and supported capabilities — see the side-by-side table on this page for the exact figures, refreshed nightly.