Gemini 3 Pro Pro vs GPT-5.2: which model should you choose?
We compared Gemini 3 Pro Pro and GPT-5.2 on price, context window and 12 benchmarks. GPT-5.2 has the stronger average benchmark score; GPT-5.2 is cheaper on a blended 3:1 basis.
Gemini 3 Pro Pro
Gemini 3 Pro Pro is a frontier model from Google DeepMind. It offers a 200,000-token context window, costs $19.80 per million input tokens and $108.61 per million output tokens, and averages 87.3 across the index's benchmark suite.
- Input
- $19.80 / 1M
- Output
- $108.61 / 1M
- Context
- 200,000
- Avg score
- 87.3
- Open weights
- No
GPT-5.2
GPT-5.2 is a frontier model from OpenAI. It offers a 2,000,000-token context window, costs $19.71 per million input tokens and $85.71 per million output tokens, and averages 88.0 across the index's benchmark suite.
- Input
- $19.71 / 1M
- Output
- $85.71 / 1M
- Context
- 2,000,000
- Avg score
- 88.0
- Open weights
- No
Specification comparison
| Spec | Gemini 3 Pro Pro | GPT-5.2 | Edge |
|---|---|---|---|
| Input price / 1M | $19.80 | $19.71 | B |
| Output price / 1M | $108.61 | $85.71 | B |
| Context window | 200,000 | 2,000,000 | B |
| Max output | 8,192 | 16,384 | B |
| Average score | 87.3 | 88.0 | B |
| Arena Elo | 1484.4 | 1478.0 | A |
| Open weights | No | No | Tie |
Benchmark comparison
Gemini 3 Pro Pro wins 5, GPT-5.2 wins 7, and 0 benchmarks are tied. The table shows the modelled score for each model and the gap.
| Benchmark | Gemini 3 Pro Pro | GPT-5.2 | Gap | Winner |
|---|---|---|---|---|
| MMLU-Pro | 88.2 | 89.9 | 1.7 | GPT-5.2 |
| GPQA Diamond | 81.4 | 84.9 | 3.5 | GPT-5.2 |
| SWE-bench Verified | 75.7 | 80.2 | 4.5 | GPT-5.2 |
| HumanEval | 95.0 | 91.0 | 4.0 | Gemini 3 Pro Pro |
| MATH-500 | 91.6 | 90.6 | 1.0 | Gemini 3 Pro Pro |
| AIME 2025 | 88.0 | 90.6 | 2.6 | GPT-5.2 |
| LiveCodeBench | 83.1 | 79.7 | 3.4 | Gemini 3 Pro Pro |
| IFEval | 92.7 | 93.6 | 0.9 | GPT-5.2 |
| TruthfulQA | 87.6 | 89.7 | 2.1 | GPT-5.2 |
| HellaSwag | 93.6 | 92.6 | 1.0 | Gemini 3 Pro Pro |
| MMMU | 83.2 | 85.3 | 2.1 | GPT-5.2 |
| Arena Elo | 1484.4 | 1478.0 | 6.4 | Gemini 3 Pro Pro |
Price analysis
On a blended 3:1 input-to-output basis, Gemini 3 Pro Pro costs about $42.00 per million tokens and GPT-5.2 costs about $36.21. GPT-5.2 is roughly 14% cheaper than Gemini 3 Pro Pro. At high volume, that gap compounds quickly, so price should carry real weight unless the quality difference is decisive.
GPT-5.2 has the larger context window at 2,000,000 tokens, compared with 200,000 for Gemini 3 Pro Pro. That matters for long documents, large codebases and multi-step agent traces.
Verdict
Across 12 shared benchmarks, Gemini 3 Pro Pro wins 5, GPT-5.2 wins 7, and 0 are tied. On the index average, GPT-5.2 leads Gemini 3 Pro Pro by 0.7 points (88.0 versus 87.3).
The price picture favours GPT-5.2. The context picture favours GPT-5.2. 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 GPT-5.2 for quality-sensitive work, and check whether its price holds at your expected volume before committing.
Choose Gemini 3 Pro Pro if
- You prefer Google DeepMind's tooling or already use it.
Choose GPT-5.2 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 2,000,000-token context window.
- You need the larger 16,384-token output limit.
FAQ
Is Gemini 3 Pro Pro better than GPT-5.2?
On the index average, GPT-5.2 leads Gemini 3 Pro Pro by 0.7 points (88.0 versus 87.3). The better choice depends on price, context and your task. Gemini 3 Pro Pro wins 5 benchmarks, GPT-5.2 wins 7.
Which is cheaper, Gemini 3 Pro Pro or GPT-5.2?
GPT-5.2 is cheaper on a blended 3:1 basis at about $36.21 per million tokens, versus $42.00 for Gemini 3 Pro Pro.
Which has the larger context window?
GPT-5.2 has the larger context window at 2,000,000 tokens. Gemini 3 Pro Pro has 200,000 tokens.
Are these models open weights?
Gemini 3 Pro Pro is proprietary; GPT-5.2 is proprietary.
Which should I choose for production?
If you need a single default, start with GPT-5.2 for quality-sensitive work, and check whether its price holds at your expected volume before committing.