GPT-6 Luna is listed at one-twentieth the token price of Claude Sonnet 5.5, but the cheaper model is not a straightforward substitute. OrcaRouter’s comparison finds Luna competitive on some coding tasks, yet far behind on terminal work and slower to begin answering.
Watch Desk analysis
What happened
OrcaRouter compares the two models’ prices, latency and results across several benchmarks. Its figures put Luna at $0.10 per million input tokens and $0.50 per million output tokens, against Sonnet 5.5’s $2 and $10. On Artificial Analysis’s Intelligence Index, Sonnet scores 55 at maximum effort and Luna 28. But on FrontierCode-AA 2.0, which tests whether a model can produce a merge-ready code change, their scores are much closer: 25.7 and 25.2.
The comparison also reports a sharper gap on Terminal-Bench 4.0: Sonnet scores 43.9%, Luna 12.6%. On that same model card, Sonnet’s first response token arrives in about 10 seconds; Luna takes about 79 seconds at maximum effort.
Why it matters
The price difference is real, but it does not settle which model costs less for a particular job. OrcaRouter says the gap narrows when measured by token use on one benchmark suite, and Luna’s slower responses may matter more in interactive products than in overnight batch work.
The results point to a practical split: Luna could be worth testing for some code-editing tasks where a person reviews the result, while terminal-heavy work or fast user-facing replies may favour Sonnet. Benchmark scores are not a promise about every team’s workload, and the comparison says results can vary with the evaluation setup.
Our read
“Twenty times cheaper” is a fine opening line and a poor procurement policy. Luna looks like a candidate for carefully chosen jobs, not a universal bargain-bin replacement. Try both on your own tasks, measure cost and waiting time, and keep a human in the loop where mistakes matter.
What to watch
- Whether Luna’s close FrontierCode result holds on teams’ own repositories.
- How the models compare on the same task with the same tools and settings.
- Whether lower effort settings make Luna responsive enough for interactive use.
Discussion spark: Would you use a model that is much cheaper but slower and less consistent for some tasks, or is predictable performance worth paying more for?
Sources and evidence
- GPT-6 Luna vs Claude Sonnet 5.5: prezzo 20x, due divari – OrcaRouter (13 November 2026, 19:15 UTC)
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