Gemini 2.5 Pro vs OpenAI o3
Gemini 2.5 Pro is cheaper for every workload modelled here.
List prices checked
Specifications and rates
| Property | Gemini 2.5 Pro | OpenAI o3 |
|---|---|---|
| Input per 1M | $1.25 | $2.00 |
| Output per 1M | $10.00 | $8.00 |
| Cached input per 1M | $0.310 | $0.500 |
| Blended (3:1) | $3.44 | $3.50 |
| Context window | 1M | 200K |
| Max output | 66K | 100K |
| Inputs accepted | text, image, audio, video | text, image |
Source: Google pricing (May 2026) · OpenAI pricing (May 2026). Published list prices only — committed-use discounts, regional variation, and per-request charges are not included. Not yet independently re-checked against the vendor’s page.
Monthly cost by workload
Identical token volumes through both rate cards. Output-heavy profiles are where the ranking flips.
| Workload | Gemini 2.5 Pro | OpenAI o3 | Cheaper |
|---|---|---|---|
| In-app chat assistantA support or help assistant handling a few thousand conversations a month, with short prompts and short answers. | $75 | $80 | Gemini 2.5 Prosaves $5.00/mo (6%) |
| RAG over documentsRetrieval-augmented answering where each request stuffs several retrieved passages into the prompt, so input dominates. | $525 | $720 | Gemini 2.5 Prosaves $195/mo (27%) |
| Coding agentAn agentic loop that reads files and writes patches, generating heavy output and re-sending large context on every turn. | $1,500 | $1,600 | Gemini 2.5 Prosaves $100/mo (6%) |
What each one is for
Gemini 2.5 Pro
by Google
A million-token context window with native video and audio input, priced at frontier-model rates below 200k tokens and at a higher tier above it — a detail that surprises people modelling long-context costs.
OpenAI o3
by OpenAI
A reasoning model that spends tokens thinking before answering. The list price understates the real cost, because reasoning tokens bill as output and can dominate the total.
Common questions
- Is Gemini 2.5 Pro or OpenAI o3 cheaper in 2026?
- Gemini 2.5 Pro, for every workload modelled here. On a blended 3:1 basis it costs $3.44 per million tokens against OpenAI o3's $3.50.
- Which has the larger context window?
- Gemini 2.5 Pro, at 1M tokens against 200K. A larger window only helps if you can afford to fill it — the cost of one full-context request is in the table above.
- Which is cheaper for output-heavy work like agents?
- OpenAI o3, at $8.00 per million output tokens against $10.00. Reasoning tokens bill as output, so for agentic loops this axis usually decides the invoice regardless of what the input rates look like.
- What is not included in these figures?
- Batch-processing discounts, fine-tuning, long-context surcharges above a provider's standard tier, and any enterprise agreement. These are published pay-as-you-go list prices, checked against each provider's own pricing page on the date shown.
- Is switching from OpenAI o3 to Gemini 2.5 Pro worth it?
- On price alone it is about 2% cheaper on a blended basis. Whether that survives contact with your workload depends on output quality and on retry rate — a cheaper model that needs two attempts is not cheaper. Model the specific volumes in the calculator before you migrate.