GoogleGemini 3.1 ProVSOpenAIGPT-5.6 Luna

Analysis by:the whichllmmodel Editorial Team|Updated: June 2026

Our Take

GPT-5.6 Luna is the superior choice here. It holds a 5.3% average lead in benchmarks while actually being more cost-effective (saving 2.0x on API costs compared to Gemini 3.1 Pro). Unless you have specific provider lock-in, go with GPT-5.6 Luna.

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Model Specs

Gemini 3.1 Pro

Website

Benchmarks & Scores

Coding (swe-bench-pro)

54.2%

excellent at multi-file repositories, autonomous agents, and industrial codebases

Reasoning (gpqa-diamond)Winner (+2.0%)

94.3%

graduate-level science QA

Cost & Context

Cost (per 1M tokens)

$4.50Input: $2.00 | Output: $12.00

Context Window

1.05M tokens

Model Specs

GPT-5.6 Luna

Website

Benchmarks & Scores

Coding (swe-bench-pro)Winner (+8.5%)

62.7%

excellent at multi-file repositories, autonomous agents, and industrial codebases

Reasoning (gpqa-diamond)

92.3%

graduate-level science QA

Cost & Context

Cost (per 1M tokens)2.0x cheaper

$2.25Input: $1.00 | Output: $6.00

Context WindowLarger

1.05M tokens

Read our data collection methodology

Frequently Asked Questions about Gemini 3.1 Pro vs GPT-5.6 Luna

GPT-5.6 Luna is cheaper than Gemini 3.1 Pro. GPT-5.6 Luna has a blended cost of $2.25/1M tokens, which is about 2.0x cheaper than Gemini 3.1 Pro at $4.50/1M tokens.

GPT-5.6 Luna is better for coding tasks on this benchmark. It scores 62.7% on swe-bench-pro (excellent at multi-file repositories, autonomous agents, and industrial codebases) compared to Gemini 3.1 Pro which scores 54.2%.

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