Anthropic and OpenAI debuted more affordable versions of their frontier models as they battle for wallet share from increasingly cost-conscious businesses, and face growing competition from lower cost open weight models. The releases came within hours of each other, a sign of the labs’ heated rivalry, despite both companies’ recent calls for an AI slowdown.
Anthropic debuted Claude Opus 5.5, which it says performs at the level of its flagship Fable 5.1 model but costs around 40% less to run than Opus 5, which came out in July. It’s the first release in a new family of models, with Sonnet 5.5 and Haiku 5.5 expected “over the coming weeks,” Anthropic said.
Anthropic said the model is its most efficient, and it’s “passing these efficiency savings on to our customers in the form of price cuts and rate limit increases.”
OpenAI released GPT-6 Sol and GPT-6 Luna, offshoots of its flagship GPT-6 Astra model that came out earlier this month. The idea is to offer a version of Astra for everyday work, OpenAI said. It also slashed the API cost by 50% lower than the pricing on a promotion it’s currently running for Astra’s predecessor, GPT-5.6. OpenAI often releases lower priced versions of its flagship models, as it did with GPT-5.6.
OpenAI’s release offers lower API pricing than Anthropic’s, based on each company’s announcement, as shown in the table below. OpenAI attributes the cost reductions to “improvements in caching and inference,” and, like Anthropic, says it’s also “passing those savings directly onto users and customers.”
The two labs are already deep into an all-out price war—something that could put pressure on their ability to profit from their models down the line.
“OpenAI and Anthropic are engaged in a price war that is driving down the price of AI and therefore driving down their ability to profit from it and grow the price of models,” Ara Kharazian, lead economist at Ramp, told Fortune.
The battle is playing out on two fronts, Kharazian said: the labs are rolling out cheaper models that businesses are shifting toward, such as Opus 5.5 and GPT-6 Sol and Luna, while also announcing outright price cuts on their most expensive ones.
That dynamic is how technology markets have traditionally worked, he said, but it’s something that more bullish investors may not be factoring in.
“AI bulls assume that there will be highly performant models that provide more and more value, and therefore they should be more expensive,” Kharazian said. “But that is not how normal technology makes it to market.”
An AI slowdown?
These are the first model releases since both companies publicly called for a coordinated attempt to “pace the frontier,” or slow the development of the most advanced models. Anthropic CEO Dario Amodei published a blog post laying out his plan for a slowdown in mid-September, which OpenAI CEO Sam Altman supported in an X post—a rare moment of solidarity between the two.
Anthropic acknowledged that the release of Opus 5.5 is its first since Amodei’s call to “pace the frontier.” The company said that Opus 5.5 underwent the company’s most rigorous alignment testing to date and was evaluated by outside groups. The model also is also launching with the same tier of cybersecurity, biology, and frontier-AI-development safeguards previously reserved for the company’s more advanced model Fable 5.1.
While today’s releases from both companies are not frontier models, as in they are not a major step up in capabilities, they show that both companies continue to push AI capabilities forward outside of the frontier. The real fight for the future of their businesses could be in gaining everyday business customers, not necessarily offering the most powerful (and expensive) models possible.
Many businesses are tightening their AI wallets and applying more scrutiny to the ROI of the technology, Randall Hunt, CTO at the AI consulting company Caylent, said.
“CFOs have seen some of the sticker shock, and they haven’t seen some of the gains that were promised in the initial investments,” Hunt said. “So they’re coming back to their planning for 2027 and beyond, and saying, ‘How can we optimize our costs here?’”
One way Caylent is doing this is by calculating how long it takes employees to complete tasks with AI tools, and then calculating “cost per task,” an approach OpenAI encouraged in a mid-July 2026 blog post as well.
