OpenAI on Tuesday released GPT-6 Sol and Luna, which will complement the flagship GPT-6 Astra model in OpenAI’s lineup. As of now, there is no GPT-6 Terra.
The headline news here is that OpenAI cut the price per million input/output tokens by half or more, compared to the previous version. GPT-6 Sol will cost $2/$10 per million input/output tokens (vs. $4/$20 for GPT-5.6 Sol), and GPT-6 Luna will come in at $0.10/$0.50 (vs. $0.20/$1.20).
The GPT-5.6 pricing was always meant to be promotional, but for the new GPT-6 models, this is the default price, an OpenAI spokesperson tells The New Stack.
“Improvements in caching and inference let us serve these models at lower cost, and we’re passing those savings directly on to users and customers,” OpenAI explains in its announcement.
As you would expect, the new models show clear improvements over the GPT-5.6 predecessors, but for the most part, these are not all that extreme.
On a benchmark like Zapier’s AutomationBench — which checks how well the models work on a set of business workflow tests — GPT-6 Luna improves by 5.4 percentage points over the previous version, for example
On the DeepSWE v1.1 software engineering benchmark, GPT-6 Sol essentially matches Anthropic’s Fable (68.8% at max effort vs. 69.9% for Fable 5 at xhigh effort), but at only 20% of the cost. Luna, at max effort, hits scores similar to Claude Opus 5 and Fable 5 at medium effort, at a significantly lower cost.
And OpenAI focuses on this cost comparison across its announcement—with a special focus on price per task instead of straight-up token pricing.
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