OpenAIGPT-5.6 LunaVSOpenAIGPT-5.6 Sol

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

Our Take

Both models perform almost identically, with an average score gap of just 2.1%. We recommend choosing GPT-5.6 Luna as it is the more cost-effective option (being 5.0x cheaper) without sacrificing any real-world capability.

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Model Specs

GPT-5.6 Luna

Website

Benchmarks & Scores

Coding (swe-bench-pro)

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)5.0x cheaper

$2.25Input: $1.00 | Output: $6.00

Context Window

1.05M tokens

Model Specs

GPT-5.6 Sol

Website

Benchmarks & Scores

Coding (swe-bench-pro)Winner (+1.9%)

64.6%

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

Reasoning (gpqa-diamond)Winner (+2.3%)

94.6%

graduate-level science QA

Cost & Context

Cost (per 1M tokens)

$11.25Input: $5.00 | Output: $30.00

Context Window

1.05M tokens

Read our data collection methodology

Frequently Asked Questions about GPT-5.6 Luna vs GPT-5.6 Sol

GPT-5.6 Luna is cheaper than GPT-5.6 Sol. GPT-5.6 Luna has a blended cost of $2.25/1M tokens, which is about 5.0x cheaper than GPT-5.6 Sol at $11.25/1M tokens.

GPT-5.6 Sol is better for coding tasks on this benchmark. It scores 64.6% on swe-bench-pro (excellent at multi-file repositories, autonomous agents, and industrial codebases) compared to GPT-5.6 Luna which scores 62.7%.

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