Gemini 2.5 Pro Max vs o3: which model should you choose?
We compared Gemini 2.5 Pro Max and o3 on price, context window and 12 benchmarks. Gemini 2.5 Pro Max has the stronger average benchmark score; Gemini 2.5 Pro Max is cheaper on a blended 3:1 basis.
Gemini 2.5 Pro Max
Gemini 2.5 Pro Max is a frontier model from Google DeepMind. It offers a 200,000-token context window, costs $16.94 per million input tokens and $64.80 per million output tokens, and averages 84.8 across the index's benchmark suite.
- Input
- $16.94 / 1M
- Output
- $64.80 / 1M
- Context
- 200,000
- Avg score
- 84.8
- 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 Max | o3 | Edge |
|---|---|---|---|
| Input price / 1M | $16.94 | $16.80 | B |
| Output price / 1M | $64.80 | $81.80 | A |
| Context window | 200,000 | 400,000 | B |
| Max output | 65,536 | 4,096 | A |
| Average score | 84.8 | 84.5 | A |
| Arena Elo | 1450.2 | 1449.0 | A |
| Open weights | No | No | Tie |
Benchmark comparison
Gemini 2.5 Pro Max wins 7, o3 wins 5, and 0 benchmarks are tied. The table shows the modelled score for each model and the gap.
| Benchmark | Gemini 2.5 Pro Max | o3 | Gap | Winner |
|---|---|---|---|---|
| MMLU-Pro | 86.7 | 86.9 | 0.2 | o3 |
| GPQA Diamond | 79.8 | 78.3 | 1.5 | Gemini 2.5 Pro Max |
| SWE-bench Verified | 75.5 | 72.9 | 2.6 | Gemini 2.5 Pro Max |
| HumanEval | 87.0 | 89.8 | 2.8 | o3 |
| MATH-500 | 91.6 | 87.9 | 3.7 | Gemini 2.5 Pro Max |
| AIME 2025 | 82.6 | 84.4 | 1.8 | o3 |
| LiveCodeBench | 79.9 | 80.7 | 0.8 | o3 |
| IFEval | 91.3 | 88.7 | 2.6 | Gemini 2.5 Pro Max |
| TruthfulQA | 85.5 | 84.6 | 0.9 | Gemini 2.5 Pro Max |
| HellaSwag | 92.9 | 92.7 | 0.2 | Gemini 2.5 Pro Max |
| MMMU | 79.7 | 82.3 | 2.6 | o3 |
| Arena Elo | 1450.2 | 1449.0 | 1.2 | Gemini 2.5 Pro Max |
Price analysis
On a blended 3:1 input-to-output basis, Gemini 2.5 Pro Max costs about $28.91 per million tokens and o3 costs about $33.05. Gemini 2.5 Pro Max is roughly 13% cheaper than o3. At high volume, that gap compounds quickly, so price should carry real weight unless the quality difference is decisive.
o3 has the larger context window at 400,000 tokens, compared with 200,000 for Gemini 2.5 Pro Max. That matters for long documents, large codebases and multi-step agent traces.
Verdict
Across 12 shared benchmarks, Gemini 2.5 Pro Max wins 7, o3 wins 5, and 0 are tied. On the index average, Gemini 2.5 Pro Max leads o3 by 0.3 points (84.8 versus 84.5).
The price picture favours Gemini 2.5 Pro Max. The context picture favours o3. 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 Gemini 2.5 Pro Max for quality-sensitive work, and check whether its price holds at your expected volume before committing.
Choose Gemini 2.5 Pro Max if
- You want the higher average benchmark score in this index.
- Unit cost matters and you want the cheaper blended price.
- You need the larger 65,536-token output limit.
Choose o3 if
- You need the larger 400,000-token context window.
FAQ
Is Gemini 2.5 Pro Max better than o3?
On the index average, Gemini 2.5 Pro Max leads o3 by 0.3 points (84.8 versus 84.5). The better choice depends on price, context and your task. Gemini 2.5 Pro Max wins 7 benchmarks, o3 wins 5.
Which is cheaper, Gemini 2.5 Pro Max or o3?
Gemini 2.5 Pro Max is cheaper on a blended 3:1 basis at about $28.91 per million tokens, versus $33.05 for o3.
Which has the larger context window?
o3 has the larger context window at 400,000 tokens. Gemini 2.5 Pro Max has 200,000 tokens.
Are these models open weights?
Gemini 2.5 Pro Max is proprietary; o3 is proprietary.
Which should I choose for production?
If you need a single default, start with Gemini 2.5 Pro Max for quality-sensitive work, and check whether its price holds at your expected volume before committing.