Why the models are missing from regular ChatGPT
GPT-6 Sol and Luna launched on September 22 in Codex, ChatGPT Work and the API. They are not new choices for ordinary Chat conversations. OpenAI’s release notes explicitly separate Work and Codex availability from Chat.
The rollout covers Plus, Pro, Business, Enterprise and Edu. Free and Go users can access Luna in the desktop app, subject to rollout and workspace settings. OpenAI positions Sol for complex coding and multi-step agent tasks, with Luna aimed at narrower, high-volume work.
API prices and the useful comparison
Standard GPT-6 Sol pricing is $2 per million input tokens and $10 per million output tokens. Luna’s rates are $0.10 and $0.50. These are API usage charges, not ChatGPT subscription prices. Our token explainer covers what those units measure.
For an identical number of tokens at those rates, Luna costs one twentieth as much as Sol. That is a price comparison, not a claim that both finish the same task equally well. A sensible first test for Luna is a repeatable job with an answer you can verify, such as sorting customer queries.
Sol does not automatically replace GPT-6 Astra either. Requests above 272,000 input tokens carry higher rates, and tools can add charges. The meaningful figure is what a completed, checked task costs after retries.
Early reactions are encouraging, not conclusive
An early r/codex discussion includes users pleased with low quota consumption on individual tasks. Another reports frustration with an answer that pointed to files instead of explaining what happened. These are launch-day anecdotes, not a shared benchmark or a representative poll.
Before switching your workflow, repeat a familiar assignment with a clear success condition. Check the output rather than accepting the model’s claim that it finished, and count the time spent correcting mistakes. We have not run our own comparative test, so these reports are not enough for us to rank Sol above its competitors.
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