OpenAI Cuts Prices on to Make High-Volume Work Economical
OpenAI has cut the price of GPT-5.6 Luna by 80%, cut the price of GPT-5.6 Terra by 20% and provided faster performance of GPT-5.6 Sol in the API while leaving its price unchanged, effective Thursday (July 30).
The company said in a Thursday blog post that it made these changes to improve the models’ performance per dollar across enterprise workloads.
Users can select the right model for the outcome they seek, balancing the stakes, cost of error, urgency and scale of each workflow, and the changes to GPT-5.6 provides them with more flexibility to optimize that calculation, according to the post.
“The GPT-5.6 family expands the range of those choices,” OpenAI said in the post. “Businesses can apply the maximum useful intelligence at every stage while paying the right price for the value it creates.”
OpenAI described GPT-5.6 Luna as its fastest and most affordable model, GPT-5.6 Terra as its balanced model for everyday work, and Sol as its frontier model.
“We are building a resilient infrastructure portfolio and matching each workload to the systems best suited to run it,” OpenAI said. “That approach supports both ends of the price-performance curve. At the lower-cost end, the new Luna and Terra prices make high-volume work economical at much greater scale. At the frontier end, Fast mode gives API customers faster access to Sol when response time is important.”
OpenAI announced July 8 that it was publicly launching the GPT-5.6 Sol, Terra and Luna models the following day after initially limiting their release at the request of the U.S. government. The company had said on June 26 that it previewed the models’ capabilities as part of its ongoing engagement with the government.
When OpenAI released the models on July 9, OpenAI CEO Sam Altman told CNBC that GPT-5.6 Sol was 54% more token efficient on agentic coding jobs and “as good or better” than competing models on the market.
“Every enterprise now is thinking about spend and the value they’re getting in exchange for AI, and this is what we really want to do,” Altman said.
The PYMNTS Intelligence report “New Data Shows How Tech Sectors Are Turning AI Into Strategy” found that when choosing to fund AI projects over the next 12 months, a majority of firms filter the technology through their unique definition of value. The report found that 60% of cybersecurity firms, 65% of software-as-a-service firms and 65% payments firms seek near-term financial results.
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