GPT-6 Sol & Luna - Frontier AI intelligence, now at half the price
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OpenAI expands the GPT-6 family with Sol and Luna with faster, cheaper models trained like Astra. 50% lower API pricing, near-Astra factuality/coding/computer use gains, better prompt caching (90% off cached reads), and alignment improvements. Live in ChatGPT Work, Codex, and via API.

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GPT-6 Sol and Luna extend OpenAI's newest model family below Astra, trained the same way but tuned for speed and cost.
What makes it different: Sol beats Claude Opus 5 on Automation Bench at roughly 9% of the cost per task, and matches Claude Fable 5.1 on DeepSWE at about 80% lower cost. Both models also carry over Astra's alignment gains, including fewer misleading claims about their own coding work.
Key features:
50% lower API pricing than GPT-5.6 equivalents
Prompt caching improvements, 90% discount on cached input reads
Near-Astra factuality, coding, and computer-use performance
Who it's for: developers and teams running high-volume or long-running agent workflows who need frontier-level performance without frontier-level cost.
Try it via ChatGPT Work, Codex, or through the API
P.S. I hunt the latest and greatest launches in tech, SaaS and AI, follow to be notified → @rohanrecommends
Does the prompt caching for Sol and Luna work the same way as it does for Astra?
So far we’re at 5.6 sols, but if the 6-sol version turns out stronger and significantly cheaper... I am totally beyond excited! 🚀
Chat has been such a help with getting all my tasks organized and is a very helpful assistant to invest in. I've explored just a few other agents but none seem to get it the way chat does.
the "9% of the cost per task" number is the headline but for us the thing that actually matters is tokens/sec, not cost per token. we run voice agents where a model that's cheaper but 200ms slower to first token is a worse deal than a pricier one that's fast, since the caller notices the silence way before they'd notice the bill. anyone tried Sol specifically in a low-latency streaming setup yet, or is the benchmarking so far all batch/offline style tasks
Intereting to see GPT 6 Sol and Luna focused on different use cases the lower cost and faster models could be really useful for everyday AI workflows
The 90% discount on cached reads may be the bigger deal here than the headline price cut. Long-running agent work keeps pulling in the same project context, so that cost adds up quietly.