OpenAI is releasing a more budget-friendly version of its most powerful model.
On Tuesday, the company unveiled GPT-6 Sol and GPT-6 Luna, the latest additions to its lineup following the release of Astra, which has quickly become one of the world's top performing models but is also neck-and-neck with Anthropic's Fable 5.1 as one of the most expensive models. OpenAI said that GPT-6 Sol and Luna were trained with similar methods to Astra, touting advancements in factuality, coding, computer use, and alignment.
The bigger highlight, however, is the cost: These models are priced around 50% cheaper per million tokens than previous iterations of Sol and Luna.
- GPT-6 Sol costs $2 per million input tokens and $10 per million output tokens, compared to 5.6 Sol's cost of $4 per million input tokens and $20 per million output tokens.
- Meanwhile, GPT-6 Luna runs at 10 cents per million input tokens and 50 cents per million output tokens, compared to its previous generation's costs of 20 cents per million input tokens and $1.20 per million output tokens.
Though OpenAI still says Astra is its "best model across the board," GPT-6 Sol outperforms previous OpenAI models, as well as Anthropic's Claude Opus 5 on a number of benchmarks, including AutomationBench, which tests business workflows across apps, Agents' Last Exam for complex agentic workflows, and DeepSWE v1.1 for complex software-engineering tasks in real codebases.
Additionally, OpenAI said GPT-6 Sol and Luna both feature Astra's improved communication style, featuring more clarity, less jargon, slightly shorter answers and fewer "low-value details." Also as a result of Astra, these models feature improved alignment compared to previous iterations, showing significantly lower rates of circumventing warning messages, coding deception, and unauthorized agent interactions.
These models are currently available in ChatGPT Work and Codex for Plus, Pro,
Business, and Enterprise users. Free and Go users can access GPT-6 Luna in the desktop app. The models are not yet available in traditional chat.
Our Deeper View
It's clear that OpenAI is reading the tea leaves on cost. For many everyday tasks, enterprises don't want to pay for the most expensive models, no matter how powerful and capable they are. This is especially true as agentic deployments start to consume a greater amount of tokens. OpenAI is showing it is capable of bending with the trend, not only by retrofitting its state-of-the-art model for efficiency, but by cutting the cost of that model from its previous generations. Attracting users with low prices and solid performance may be OpenAI's best shot at keeping its lead and fending off innovations that threaten its bet on conventional scaling laws, such as the recent innovations from Jev, AlohaJet and Pathway that The Deep View has reported on.
