Choosing GPT-5.6 Sol, Terra, or Luna in Codex

Writing the post from only the given facts—title, model names, Codex, and HN metrics—without inventing details.

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Choosing among GPT-5.6 Sol, Terra, and Luna in Codex is the subject of a short item circulating from a post by pvncher, with a related thread on Hacker News under the Claude/Codex/Fable cluster. On HN the item sits at 1 point and 0 comments, so public discussion has not yet added consensus, counterexamples, or measured comparisons.

Codex is the surface where the choice is made: three GPT-5.6 options labeled Sol, Terra, and Luna. The labels alone do not specify size, latency, tool-use behavior, or pricing tiers. Without those specs in the source material, the technical distinction is naming and product packaging rather than published architecture or benchmark tables.

For engineers already inside Codex, the practical problem is selection under incomplete public detail. Defaulting to one variant without knowing tradeoffs (speed vs. depth, cost vs. reliability, chat vs. agent workloads) risks inconsistent results across the same codebase or pipeline. Builders who treat “GPT-5.6” as a single model will miss that the product now surfaces three named paths.

Competitive context is the wider Claude/Codex/Fable conversation on HN, where model naming and IDE-adjacent tooling are already compared side by side. A 1-point, 0-comment listing means this particular angle has not yet been stress-tested by that crowd; rival tooling threads may still dominate attention until someone posts hard side-by-side runs.

Watch for official Codex docs or UI copy that maps Sol, Terra, and Luna to concrete limits (context, tools, rate, price). Until that mapping is public, treat the three names as product SKUs, not interchangeable synonyms, and pin which variant you used in any eval or production log so later switches are auditable.