whichllmmodel
Back to Dashboard

Google Gemini 2.5 Pro VS OpenAI GPT-5.6 Luna

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

Decision Recommendation

👑 Editorial Verdict: GPT-5.6 Luna strictly dominates Gemini 2.5 Pro across all compared dimensions. It is not only more cost-effective (blended cost of $2.25 vs $3.44 per 1M tokens) but also delivers superior coding accuracy (62.7% vs 59.6% on SWE-bench). Unless you have platform lock-in, GPT-5.6 Luna is the clear and optimal choice for all development workloads.
Was this recommendation helpful?
Model Specs

Gemini 2.5 Pro

Benchmarks & Scores

Coding (swe-bench-verified)
59.6%

good at editing existing code, cross-file updates, and multi-component systems

Reasoning (gpqa-diamond)
84.4%

graduate-level science QA

Cost & Performance

Cost (per 1M tokens)
$3.44Input: $1.25 | Output: $10.00
Context Window
1M tokens
Model Specs

GPT-5.6 Luna

Benchmarks & Scores

Coding (swe-bench-pro)
62.7%

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

Reasoning (gpqa-diamond)Winner (+7.9%)
92.3%

graduate-level science QA

Cost & Performance

Cost (per 1M tokens)1.5x cheaper
$2.25Input: $1.00 | Output: $6.00
Context WindowLarger
1.05M tokens

Frequently Asked Questions about Gemini 2.5 Pro vs GPT-5.6 Luna comparison

GPT-5.6 Luna is cheaper than Gemini 2.5 Pro. GPT-5.6 Luna has a blended cost of $2.25/1M tokens, which is about 1.5x cheaper than Gemini 2.5 Pro at $3.44/1M tokens.

For coding tasks, Gemini 2.5 Pro scores 59.6% on swe-bench-verified (good at editing existing code, cross-file updates, and multi-component systems), while GPT-5.6 Luna scores 62.7% on swe-bench-pro (excellent at multi-file repositories, autonomous agents, and industrial codebases).