Gemini 3 Pro vs GPT-5.2 Vision: which model should you choose?
We compared Gemini 3 Pro and GPT-5.2 Vision on price, context window and 12 benchmarks. GPT-5.2 Vision has the stronger average benchmark score; Gemini 3 Pro 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
GPT-5.2 Vision
GPT-5.2 Vision is a frontier model from OpenAI. It offers a 1,000,000-token context window, costs $19.03 per million input tokens and $85.72 per million output tokens, and averages 87.4 across the index's benchmark suite.
- Input
- $19.03 / 1M
- Output
- $85.72 / 1M
- Context
- 1,000,000
- Avg score
- 87.4
- Open weights
- No
Specification comparison
| Spec | Gemini 3 Pro | GPT-5.2 Vision | Edge |
|---|---|---|---|
| Input price / 1M | $18.24 | $19.03 | A |
| Output price / 1M | $82.93 | $85.72 | A |
| Context window | 2,000,000 | 1,000,000 | A |
| Max output | 8,192 | 16,384 | B |
| Average score | 86.1 | 87.4 | B |
| Arena Elo | 1460.7 | 1484.3 | B |
| Open weights | No | No | Tie |
Benchmark comparison
Gemini 3 Pro wins 2, GPT-5.2 Vision wins 10, and 0 benchmarks are tied. The table shows the modelled score for each model and the gap.
| Benchmark | Gemini 3 Pro | GPT-5.2 Vision | Gap | Winner |
|---|---|---|---|---|
| MMLU-Pro | 88.2 | 89.5 | 1.3 | GPT-5.2 Vision |
| GPQA Diamond | 79.0 | 82.1 | 3.1 | GPT-5.2 Vision |
| SWE-bench Verified | 78.5 | 78.8 | 0.3 | GPT-5.2 Vision |
| HumanEval | 91.8 | 91.2 | 0.6 | Gemini 3 Pro |
| MATH-500 | 89.9 | 92.9 | 3.0 | GPT-5.2 Vision |
| AIME 2025 | 84.3 | 85.7 | 1.4 | GPT-5.2 Vision |
| LiveCodeBench | 83.3 | 83.4 | 0.1 | GPT-5.2 Vision |
| IFEval | 93.7 | 93.9 | 0.2 | GPT-5.2 Vision |
| TruthfulQA | 88.8 | 85.3 | 3.5 | Gemini 3 Pro |
| HellaSwag | 91.3 | 94.6 | 3.3 | GPT-5.2 Vision |
| MMMU | 78.6 | 84.4 | 5.8 | GPT-5.2 Vision |
| Arena Elo | 1460.7 | 1484.3 | 23.6 | GPT-5.2 Vision |
Price analysis
On a blended 3:1 input-to-output basis, Gemini 3 Pro costs about $34.41 per million tokens and GPT-5.2 Vision costs about $35.70. Gemini 3 Pro is roughly 4% cheaper than GPT-5.2 Vision. At high volume, that gap compounds quickly, so price should carry real weight unless the quality difference is decisive.
Gemini 3 Pro has the larger context window at 2,000,000 tokens, compared with 1,000,000 for GPT-5.2 Vision. That matters for long documents, large codebases and multi-step agent traces.
Verdict
Across 12 shared benchmarks, Gemini 3 Pro wins 2, GPT-5.2 Vision wins 10, and 0 are tied. On the index average, GPT-5.2 Vision leads Gemini 3 Pro by 1.3 points (87.4 versus 86.1).
The price picture favours Gemini 3 Pro. The context picture favours Gemini 3 Pro. 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 Vision for quality-sensitive work and Gemini 3 Pro 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
- Unit cost matters and you want the cheaper blended price.
- You need the larger 2,000,000-token context window.
Choose GPT-5.2 Vision if
- You want the higher average benchmark score in this index.
- You need the larger 16,384-token output limit.
FAQ
Is Gemini 3 Pro better than GPT-5.2 Vision?
On the index average, GPT-5.2 Vision leads Gemini 3 Pro by 1.3 points (87.4 versus 86.1). The better choice depends on price, context and your task. Gemini 3 Pro wins 2 benchmarks, GPT-5.2 Vision wins 10.
Which is cheaper, Gemini 3 Pro or GPT-5.2 Vision?
Gemini 3 Pro is cheaper on a blended 3:1 basis at about $34.41 per million tokens, versus $35.70 for GPT-5.2 Vision.
Which has the larger context window?
Gemini 3 Pro has the larger context window at 2,000,000 tokens. GPT-5.2 Vision has 1,000,000 tokens.
Are these models open weights?
Gemini 3 Pro is proprietary; GPT-5.2 Vision is proprietary.
Which should I choose for production?
If you need a single default, start with GPT-5.2 Vision for quality-sensitive work and Gemini 3 Pro for high-volume, well-scoped tasks. Run both on a sample of your own traffic before locking in a choice.