Gemini 2.5 Pro Pro vs o3: which model should you choose?
We compared Gemini 2.5 Pro Pro and o3 on price, context window and 12 benchmarks. o3 has the stronger average benchmark score; o3 is cheaper on a blended 3:1 basis.
Gemini 2.5 Pro Pro
Gemini 2.5 Pro Pro is a frontier model from Google DeepMind. It offers a 400,000-token context window, costs $17.16 per million input tokens and $90.89 per million output tokens, and averages 83.6 across the index's benchmark suite.
- Input
- $17.16 / 1M
- Output
- $90.89 / 1M
- Context
- 400,000
- Avg score
- 83.6
- Open weights
- No
o3
o3 is a frontier model from OpenAI. It offers a 400,000-token context window, costs $16.80 per million input tokens and $81.80 per million output tokens, and averages 84.5 across the index's benchmark suite.
- Input
- $16.80 / 1M
- Output
- $81.80 / 1M
- Context
- 400,000
- Avg score
- 84.5
- Open weights
- No
Specification comparison
| Spec | Gemini 2.5 Pro Pro | o3 | Edge |
|---|---|---|---|
| Input price / 1M | $17.16 | $16.80 | B |
| Output price / 1M | $90.89 | $81.80 | B |
| Context window | 400,000 | 400,000 | Tie |
| Max output | 8,192 | 4,096 | A |
| Average score | 83.6 | 84.5 | B |
| Arena Elo | 1460.2 | 1449.0 | A |
| Open weights | No | No | Tie |
Benchmark comparison
Gemini 2.5 Pro Pro wins 4, o3 wins 8, and 0 benchmarks are tied. The table shows the modelled score for each model and the gap.
| Benchmark | Gemini 2.5 Pro Pro | o3 | Gap | Winner |
|---|---|---|---|---|
| MMLU-Pro | 85.2 | 86.9 | 1.7 | o3 |
| GPQA Diamond | 81.6 | 78.3 | 3.3 | Gemini 2.5 Pro Pro |
| SWE-bench Verified | 72.1 | 72.9 | 0.8 | o3 |
| HumanEval | 88.4 | 89.8 | 1.4 | o3 |
| MATH-500 | 86.8 | 87.9 | 1.1 | o3 |
| AIME 2025 | 83.3 | 84.4 | 1.1 | o3 |
| LiveCodeBench | 76.5 | 80.7 | 4.2 | o3 |
| IFEval | 92.0 | 88.7 | 3.3 | Gemini 2.5 Pro Pro |
| TruthfulQA | 85.5 | 84.6 | 0.9 | Gemini 2.5 Pro Pro |
| HellaSwag | 90.6 | 92.7 | 2.1 | o3 |
| MMMU | 78.1 | 82.3 | 4.2 | o3 |
| Arena Elo | 1460.2 | 1449.0 | 11.2 | Gemini 2.5 Pro Pro |
Price analysis
On a blended 3:1 input-to-output basis, Gemini 2.5 Pro Pro costs about $35.59 per million tokens and o3 costs about $33.05. o3 is roughly 7% cheaper than Gemini 2.5 Pro Pro. At high volume, that gap compounds quickly, so price should carry real weight unless the quality difference is decisive.
Both models list a 400,000-token context window. That is enough for long documents, large codebases and multi-step agent traces.
Verdict
Across 12 shared benchmarks, Gemini 2.5 Pro Pro wins 4, o3 wins 8, and 0 are tied. On the index average, o3 leads Gemini 2.5 Pro Pro by 0.9 points (84.5 versus 83.6).
The price picture favours o3. The context picture is effectively a tie. Those two dimensions often matter more than a few benchmark points once a model is good enough for the task.
If you need a single default, start with o3 for quality-sensitive work, and check whether its price holds at your expected volume before committing.
Choose Gemini 2.5 Pro Pro if
- You need the larger 8,192-token output limit.
Choose o3 if
- You want the higher average benchmark score in this index.
- Unit cost matters and you want the cheaper blended price.
FAQ
Is Gemini 2.5 Pro Pro better than o3?
On the index average, o3 leads Gemini 2.5 Pro Pro by 0.9 points (84.5 versus 83.6). The better choice depends on price, context and your task. Gemini 2.5 Pro Pro wins 4 benchmarks, o3 wins 8.
Which is cheaper, Gemini 2.5 Pro Pro or o3?
o3 is cheaper on a blended 3:1 basis at about $33.05 per million tokens, versus $35.59 for Gemini 2.5 Pro Pro.
Which has the larger context window?
Both models list a 400,000-token context window.
Are these models open weights?
Gemini 2.5 Pro Pro is proprietary; o3 is proprietary.
Which should I choose for production?
If you need a single default, start with o3 for quality-sensitive work, and check whether its price holds at your expected volume before committing.