Head-to-head · frontier vs frontier

Gemini 3 Pro Vision vs GPT-4.1 Pro: which model should you choose?

We compared Gemini 3 Pro Vision and GPT-4.1 Pro on price, context window and 12 benchmarks. Gemini 3 Pro Vision has the stronger average benchmark score; Gemini 3 Pro Vision is cheaper on a blended 3:1 basis.

Google DeepMind

Gemini 3 Pro Vision

Gemini 3 Pro Vision is a frontier model from Google DeepMind. It offers a 200,000-token context window, costs $17.59 per million input tokens and $68.83 per million output tokens, and averages 85.5 across the index's benchmark suite.

Input
$17.59 / 1M
Output
$68.83 / 1M
Context
200,000
Avg score
85.5
Open weights
No
Full Gemini 3 Pro Vision page
OpenAI

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
Full GPT-4.1 Pro page

Specification comparison

SpecGemini 3 Pro VisionGPT-4.1 ProEdge
Input price / 1M$17.59$17.56B
Output price / 1M$68.83$91.14A
Context window200,000400,000B
Max output128,0008,192A
Average score85.585.2A
Arena Elo1458.11449.6A
Open weightsNoNoTie

Benchmark comparison

Gemini 3 Pro Vision wins 6, GPT-4.1 Pro wins 6, and 0 benchmarks are tied. The table shows the modelled score for each model and the gap.

BenchmarkGemini 3 Pro VisionGPT-4.1 ProGapWinner
MMLU-Pro87.386.90.4Gemini 3 Pro Vision
GPQA Diamond80.678.22.4Gemini 3 Pro Vision
SWE-bench Verified76.577.30.8GPT-4.1 Pro
HumanEval91.691.90.3GPT-4.1 Pro
MATH-50088.488.80.4GPT-4.1 Pro
AIME 202587.382.84.5Gemini 3 Pro Vision
LiveCodeBench79.276.72.5Gemini 3 Pro Vision
IFEval90.492.21.8GPT-4.1 Pro
TruthfulQA84.587.73.2GPT-4.1 Pro
HellaSwag91.193.72.6GPT-4.1 Pro
MMMU83.681.52.1Gemini 3 Pro Vision
Arena Elo1458.11449.68.5Gemini 3 Pro Vision

Price analysis

On a blended 3:1 input-to-output basis, Gemini 3 Pro Vision costs about $30.40 per million tokens and GPT-4.1 Pro costs about $35.95. Gemini 3 Pro Vision is roughly 15% 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 Pro Vision. That matters for long documents, large codebases and multi-step agent traces.

Verdict

Across 12 shared benchmarks, Gemini 3 Pro Vision wins 6, GPT-4.1 Pro wins 6, and 0 are tied. On the index average, Gemini 3 Pro Vision leads GPT-4.1 Pro by 0.3 points (85.5 versus 85.2).

The price picture favours Gemini 3 Pro Vision. 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 Gemini 3 Pro Vision for quality-sensitive work, and check whether its price holds at your expected volume before committing.

Choose Gemini 3 Pro Vision 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 128,000-token output limit.

Choose GPT-4.1 Pro if

  • You need the larger 400,000-token context window.

FAQ

Is Gemini 3 Pro Vision better than GPT-4.1 Pro?

On the index average, Gemini 3 Pro Vision leads GPT-4.1 Pro by 0.3 points (85.5 versus 85.2). The better choice depends on price, context and your task. Gemini 3 Pro Vision wins 6 benchmarks, GPT-4.1 Pro wins 6.

Which is cheaper, Gemini 3 Pro Vision or GPT-4.1 Pro?

Gemini 3 Pro Vision is cheaper on a blended 3:1 basis at about $30.40 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 Pro Vision has 200,000 tokens.

Are these models open weights?

Gemini 3 Pro Vision is proprietary; GPT-4.1 Pro is proprietary.

Which should I choose for production?

If you need a single default, start with Gemini 3 Pro Vision for quality-sensitive work, and check whether its price holds at your expected volume before committing.

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