GPT-5.6 Luna and Gemini 3.6 Flash: A Cost Counterexample in Document-Vision Tasks

Summary

The post title uses a benchmark to claim that Luna is better than Google's models, but the comments provide an important production counterexample: in PDF document auditing, classification, question answering, and bounding-box tasks, one commenter considers Gemini 3.6 Flash more stable and better at following instructions, at a monthly cost of about $7,000; Luna is estimated at about $2,000, but its vision capabilities and bounding-box quality are worse.

Results and takeaways

• Benchmark rankings may not align with specific vision workflows.

• Luna has a clear price advantage, but lower cost does not mean a higher acceptance rate in vision tasks.

• Real-world evaluations should record instruction following, bounding-box localization accuracy, classification accuracy, manual rework, and total monthly cost at the same time.

• The monthly costs in this post are user estimates, not the results of a standardized API test.

Original article

GPT 5.6 Luna is now Better than Google's Best Model and Cheaper than Google's Cheapest Model Intelligence index taken fr… This is a necessary excerpt; read the original source for full context.