Gemini 3 Pro vs o4: which model should you choose?
We compared Gemini 3 Pro and o4 on price, context window and 12 benchmarks. Gemini 3 Pro has the stronger average benchmark score; o4 is cheaper on a blended 3:1 basis.
Gemini 3 Pro
Gemini 3 Pro is a frontier model from Google DeepMind. It offers a 2,000,000-token context window, costs $18.24 per million input tokens and $82.93 per million output tokens, and averages 86.1 across the index's benchmark suite.
- Input
- $18.24 / 1M
- Output
- $82.93 / 1M
- Context
- 2,000,000
- Avg score
- 86.1
- Open weights
- No
o4
o4 is a frontier model from OpenAI. It offers a 2,000,000-token context window, costs $17.74 per million input tokens and $66.00 per million output tokens, and averages 85.4 across the index's benchmark suite.
- Input
- $17.74 / 1M
- Output
- $66.00 / 1M
- Context
- 2,000,000
- Avg score
- 85.4
- Open weights
- No
Specification comparison
| Spec | Gemini 3 Pro | o4 | Edge |
|---|---|---|---|
| Input price / 1M | $18.24 | $17.74 | B |
| Output price / 1M | $82.93 | $66.00 | B |
| Context window | 2,000,000 | 2,000,000 | Tie |
| Max output | 8,192 | 8,192 | Tie |
| Average score | 86.1 | 85.4 | A |
| Arena Elo | 1460.7 | 1469.4 | B |
| Open weights | No | No | Tie |
Benchmark comparison
Gemini 3 Pro wins 7, o4 wins 5, and 0 benchmarks are tied. The table shows the modelled score for each model and the gap.
| Benchmark | Gemini 3 Pro | o4 | Gap | Winner |
|---|---|---|---|---|
| MMLU-Pro | 88.2 | 85.3 | 2.9 | Gemini 3 Pro |
| GPQA Diamond | 79.0 | 82.3 | 3.3 | o4 |
| SWE-bench Verified | 78.5 | 74.8 | 3.7 | Gemini 3 Pro |
| HumanEval | 91.8 | 89.6 | 2.2 | Gemini 3 Pro |
| MATH-500 | 89.9 | 90.5 | 0.6 | o4 |
| AIME 2025 | 84.3 | 85.3 | 1.0 | o4 |
| LiveCodeBench | 83.3 | 81.4 | 1.9 | Gemini 3 Pro |
| IFEval | 93.7 | 92.8 | 0.9 | Gemini 3 Pro |
| TruthfulQA | 88.8 | 85.0 | 3.8 | Gemini 3 Pro |
| HellaSwag | 91.3 | 91.0 | 0.3 | Gemini 3 Pro |
| MMMU | 78.6 | 80.9 | 2.3 | o4 |
| Arena Elo | 1460.7 | 1469.4 | 8.7 | o4 |
Price analysis
On a blended 3:1 input-to-output basis, Gemini 3 Pro costs about $34.41 per million tokens and o4 costs about $29.80. o4 is roughly 13% cheaper than Gemini 3 Pro. At high volume, that gap compounds quickly, so price should carry real weight unless the quality difference is decisive.
Both models list a 2,000,000-token context window. That is enough for long documents, large codebases and multi-step agent traces.
Verdict
Across 12 shared benchmarks, Gemini 3 Pro wins 7, o4 wins 5, and 0 are tied. On the index average, Gemini 3 Pro leads o4 by 0.7 points (86.1 versus 85.4).
The price picture favours o4. 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 Gemini 3 Pro for quality-sensitive work and o4 for high-volume, well-scoped tasks. Run both on a sample of your own traffic before locking in a choice.
Choose Gemini 3 Pro if
- You want the higher average benchmark score in this index.
Choose o4 if
- Unit cost matters and you want the cheaper blended price.
FAQ
Is Gemini 3 Pro better than o4?
On the index average, Gemini 3 Pro leads o4 by 0.7 points (86.1 versus 85.4). The better choice depends on price, context and your task. Gemini 3 Pro wins 7 benchmarks, o4 wins 5.
Which is cheaper, Gemini 3 Pro or o4?
o4 is cheaper on a blended 3:1 basis at about $29.80 per million tokens, versus $34.41 for Gemini 3 Pro.
Which has the larger context window?
Both models list a 2,000,000-token context window.
Are these models open weights?
Gemini 3 Pro is proprietary; o4 is proprietary.
Which should I choose for production?
If you need a single default, start with Gemini 3 Pro for quality-sensitive work and o4 for high-volume, well-scoped tasks. Run both on a sample of your own traffic before locking in a choice.