Gemini 3 Flash Turbo vs GPT-4.1 Pro: which model should you choose?
We compared Gemini 3 Flash Turbo and GPT-4.1 Pro on price, context window and 12 benchmarks. GPT-4.1 Pro has the stronger average benchmark score; Gemini 3 Flash Turbo is cheaper on a blended 3:1 basis.
Gemini 3 Flash Turbo
Gemini 3 Flash Turbo is a frontier model from Google DeepMind. It offers a 200,000-token context window, costs $17.07 per million input tokens and $69.05 per million output tokens, and averages 84.1 across the index's benchmark suite.
- Input
- $17.07 / 1M
- Output
- $69.05 / 1M
- Context
- 200,000
- Avg score
- 84.1
- Open weights
- No
GPT-4.1 Pro
GPT-4.1 Pro is a frontier model from OpenAI. It offers a 400,000-token context window, costs $17.56 per million input tokens and $91.14 per million output tokens, and averages 85.2 across the index's benchmark suite.
- Input
- $17.56 / 1M
- Output
- $91.14 / 1M
- Context
- 400,000
- Avg score
- 85.2
- Open weights
- No
Specification comparison
| Spec | Gemini 3 Flash Turbo | GPT-4.1 Pro | Edge |
|---|---|---|---|
| Input price / 1M | $17.07 | $17.56 | A |
| Output price / 1M | $69.05 | $91.14 | A |
| Context window | 200,000 | 400,000 | B |
| Max output | 16,384 | 8,192 | A |
| Average score | 84.1 | 85.2 | B |
| Arena Elo | 1473.4 | 1449.6 | A |
| Open weights | No | No | Tie |
Benchmark comparison
Gemini 3 Flash Turbo wins 4, GPT-4.1 Pro wins 8, and 0 benchmarks are tied. The table shows the modelled score for each model and the gap.
| Benchmark | Gemini 3 Flash Turbo | GPT-4.1 Pro | Gap | Winner |
|---|---|---|---|---|
| MMLU-Pro | 87.9 | 86.9 | 1.0 | Gemini 3 Flash Turbo |
| GPQA Diamond | 77.5 | 78.2 | 0.7 | GPT-4.1 Pro |
| SWE-bench Verified | 72.5 | 77.3 | 4.8 | GPT-4.1 Pro |
| HumanEval | 90.6 | 91.9 | 1.3 | GPT-4.1 Pro |
| MATH-500 | 87.6 | 88.8 | 1.2 | GPT-4.1 Pro |
| AIME 2025 | 81.3 | 82.8 | 1.5 | GPT-4.1 Pro |
| LiveCodeBench | 78.5 | 76.7 | 1.8 | Gemini 3 Flash Turbo |
| IFEval | 88.9 | 92.2 | 3.3 | GPT-4.1 Pro |
| TruthfulQA | 87.4 | 87.7 | 0.3 | GPT-4.1 Pro |
| HellaSwag | 89.5 | 93.7 | 4.2 | GPT-4.1 Pro |
| MMMU | 83.0 | 81.5 | 1.5 | Gemini 3 Flash Turbo |
| Arena Elo | 1473.4 | 1449.6 | 23.8 | Gemini 3 Flash Turbo |
Price analysis
On a blended 3:1 input-to-output basis, Gemini 3 Flash Turbo costs about $30.06 per million tokens and GPT-4.1 Pro costs about $35.95. Gemini 3 Flash Turbo is roughly 16% cheaper than GPT-4.1 Pro. At high volume, that gap compounds quickly, so price should carry real weight unless the quality difference is decisive.
GPT-4.1 Pro has the larger context window at 400,000 tokens, compared with 200,000 for Gemini 3 Flash Turbo. That matters for long documents, large codebases and multi-step agent traces.
Verdict
Across 12 shared benchmarks, Gemini 3 Flash Turbo wins 4, GPT-4.1 Pro wins 8, and 0 are tied. On the index average, GPT-4.1 Pro leads Gemini 3 Flash Turbo by 1.1 points (85.2 versus 84.1).
The price picture favours Gemini 3 Flash Turbo. The context picture favours GPT-4.1 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-4.1 Pro for quality-sensitive work and Gemini 3 Flash Turbo for high-volume, well-scoped tasks. Run both on a sample of your own traffic before locking in a choice.
Choose Gemini 3 Flash Turbo if
- Unit cost matters and you want the cheaper blended price.
- You need the larger 16,384-token output limit.
Choose GPT-4.1 Pro if
- You want the higher average benchmark score in this index.
- You need the larger 400,000-token context window.
FAQ
Is Gemini 3 Flash Turbo better than GPT-4.1 Pro?
On the index average, GPT-4.1 Pro leads Gemini 3 Flash Turbo by 1.1 points (85.2 versus 84.1). The better choice depends on price, context and your task. Gemini 3 Flash Turbo wins 4 benchmarks, GPT-4.1 Pro wins 8.
Which is cheaper, Gemini 3 Flash Turbo or GPT-4.1 Pro?
Gemini 3 Flash Turbo is cheaper on a blended 3:1 basis at about $30.06 per million tokens, versus $35.95 for GPT-4.1 Pro.
Which has the larger context window?
GPT-4.1 Pro has the larger context window at 400,000 tokens. Gemini 3 Flash Turbo has 200,000 tokens.
Are these models open weights?
Gemini 3 Flash Turbo is proprietary; GPT-4.1 Pro is proprietary.
Which should I choose for production?
If you need a single default, start with GPT-4.1 Pro for quality-sensitive work and Gemini 3 Flash Turbo for high-volume, well-scoped tasks. Run both on a sample of your own traffic before locking in a choice.