Anthropic Joins AI Price War With Release of Fable 5.1

pedrosala via Getty ImagesAnthropic introduced Fable 5.1 and Mythos 5.1, highlighting how it is addressing pricing concerns for enterprise customers. However, despite the powerful capabilities of Fable 5.1 and Mythos 5.1, enterprises don’t always need the most powerful model for their workloads.The AI lab on Sept. 1 revealed that Fable 5.1 and Mythos 5.1 are the same models, except that Mythos 5.1 is accessible only to authorized users as part of its Project Glasswing cybersecurity initiative and includes distinct levels of safeguards.The vendor said that, along with increased capabilities in advanced coding and knowledge work, and improved research skills in science fields, Fable 5.1 costs 25% less than Fable 5 for typical workloads because it reduces cache read pricing. Cache read is when the model reads the inputs that have already been processed or stored. This means Fable 5.1 pricing is reduced from $1 per million tokens to $0.25 per million tokens. Other than this difference, the standard input pricing remains $10 per million input tokens and $50 per million output tokens. The standard pricing is still significantly higher than OpenAI’s GPT-5.6 Sol, which is $5 per million input tokens and $30 per million output tokens.Related:Nvidia and Semiconductor Vendor Expand PartnershipFable 5.1’s price cut reveals the vendor’s strategy in dealing with the escalating price war in the AI market. In addition to Anthropic, OpenAI, Google and Microsoft are competitively reducing their prices as the cost of AI becomes harder to contain, while enterprises are trying to determine the ROI and use cases for frontier models.“We are at a juncture where token consumption is a big concern,” said Lian Jye Su, an analyst at Omdia, a division of Informa TechTarget.Pricing and Anthropic’s IPOSu added that while vendors have begun to reduce prices, enterprises have started finding their own ways to address the pricing issue.“People are using a lot more model routing nowadays compared to just relying on a single vendor,” Su said. “The type of processes that you run will dictate what type of models you select at the end of the day. If you are someone who really needs that frontier capability, you will still go with the most complex models.”However, Anthropic’s move to reduce prices for cached reads of Fable 5.1, while also claiming that the model is the same as Mythos 5 (its most powerful and restrictive model) and that it has a separate set of safeguards, might be intended to further its IPO ambitions. Anthropic filed for an IPO on June 1 and is expected to go public this fall.Related:Anthropic Releases Interface to Help AI Agents Operate Machines“It needs to have this solid recurring revenue to ensure that its valuation continues to stay on top,” Su said.Not for All EnterprisesLower pricing, along with Fable 5.1’s improved performance, makes the model attractive to enterprises. However, enterprises should still assess whether the model is truly needed for their specific workloads.“This is definitely an announcement for companies that are looking at the most frontier capability that really care about differentiating themselves from the rest,” Su said. He added that the model is not for back-office operations or day-to-day tasks, nor for enterprises that need an on-premises option.“New models nowadays focus very strongly on agentic AI vulnerability testing or advanced challenges,” Su said. “Most of the stuff that we do with AI nowadays is not necessarily the most complicated tasks.”While enterprises may not need to use Fable 5.1, the model shows how Anthropic continues to strengthen its safety measures. The vendor revealed that until its Enterprise Frontier Safeguards are available, customers can use Fable 5.1 with zero data retention.Anthropic introduced Enterprise Frontier Safeguards on Sept. 1 as a new security standard that combines the privacy of not retaining enterprise data with the security of detecting misuse.Related:Prompt: The AI Infrastructure Boom Is Getting Bigger Than GPUsMoreover, the vendor’s newest safeguards are better at reducing false positives. False positives occur when an AI model flags a pattern or object that is not actually present or flags unimportant content.“Anthropic has always been strongly against AI that is left ungoverned,” Su said. “It’s that continual effort to ensure it stays on top of all the critical concerns in the market.”About the AuthorNews Writer, AI BusinessEsther Shittu has covered AI technologies and industry trends since 2021. As co-host of the Targeting AI podcast, she talks with experts, thought leaders and practitioners exploring critical AI developments. Before AI Business, she wrote for SearchEnterpriseAI, the New York Daily News, Bklyner and the Brooklyn Daily Eagle. When she's not diving deep into the world of AI, she spends her time on passion projects and raising her three daughters.