o3 vs Gemini 2.5 Pro pricing
Side-by-side LLM API pricing.Gemini 2.5 Pro is cheaper on input ($1.25 vs $2.00 /1M), and o3 is cheaper on output ($8.00 vs $10.00 /1M). On a blended average, o3 is lower — but which wins for you depends on your input/output mix, so check the example workloads below or run the calculator.
| Attribute | o3 | Gemini 2.5 Pro |
|---|---|---|
| Provider | OpenAI | |
| Tier | Reasoning | Flagship |
| Status | GA | GA |
| Context window | 200K | 1M |
| Input /1M | $2.00 | $1.25 |
| Output /1M | $8.00 | $10.00 |
| Cached input /1M | $0.50 | $0.125 |
| Batch input /1M | $1.00 | $0.625 |
| Batch output /1M | $4.00 | $5.00 |
| Blended (avg in+out) | $5.00 | $5.63 |
| 1M in + 1M out | $10.00 | $11.25 |
| 1M in (90% cached) + 100K out | $1.45 | $1.24 |
List prices, USD, directional. Rates are provider list prices per 1M tokens and are meant for comparison, not billing. Batch rates shown as 50% off are derived where a provider offers batch but does not publish a separate figure. Preview, promo, intro, peak/off-peak, long-context, and third-party-host prices are labeled where they apply. Token counts vary by tokenizer, so per-token price is not always a like-for-like cost. Always confirm with the provider before relying on a number. Prices as of 2026-08-03.
Which should you pick?
For a balanced job (1M input + 1M output), o3 costs $10.00 versus $11.25. If your prompts are large and reused, prompt caching changes the maths — the cache-heavy row above shows a 90%-cached input scenario. If your work can run asynchronously, both providers' batch rates cut the bill further where offered.
Full price matrices: o3 pricing → · Gemini 2.5 Pro pricing → · Back to the LLM pricing hub →