OpenAI slashes price for model again

Justin Sullivan via Getty ImagesOpenAI’s latest model, GPT-6.1 Terra, is 50% cheaper than its previous version, showing how the generative AI vendor continues to respond to price pressure from open-weight providers. However, the escalating AI model price war could become daunting for enterprises now faced with multiple models at their lowest prices.OpenAI introduced the updated model on Monday, nearly a month after releasing GPT-6.1 Sol. The new Terra model is fast and efficient, combining visual reasoning and precise use of computers, OpenAI said. The model is good at computer-based tasks such as drafting proposals, filling out forms and editing videos.However, its price is its true selling point: $1 per million input tokens and $5 per million output tokens. In comparison, GPT-6.1 Sol costs $2 per million input tokens and $10 per million output tokens. GPT-5.6 Terra also costs $2 per million input tokens and $12 per million output tokens.Related:The rise of 'agentic' in the enterprise workforceThe release of GPT-6.1 Terra marks the fourth consecutive time OpenAI has slashed the price of its models, a trend it and its chief rival Anthropic are extending as they compete against open-weight models from Chinese vendors such as Alibaba, Baidu and Z.ai. Comparatively, Anthropic, which filed its IPO prospectus with the SEC this week, has also slashed its pricing, with the most recent price cut in October, when the vendor reduced the price of Haiku 5.5 by 90% per 100K tokens and $0.50 per million output tokens.“They are refining our ability to get the most bang for our buck out of these models,” said David Nicholson, an analyst at Futurum Group. “If everything is priced at the highest level, then people will look for alternatives, so what they’re trying to do is make their tools as efficient as possible.”Lower price but more confusionMeanwhile, for model users, it’s unclear which model is right for which environment or workload, even as model makers continue to reduce prices.“We are a long way from enterprises being able to efficiently leverage the most cost-effective model for each task that they want achieved,” Nicholson said. “It’s great to have more choice, but I think the choice is causing confusion.”While cheaper models enable enterprises to optimize token consumption and cost for the work they’re doing, “there’s a friction associated with it because you have to have a certain level of understanding and insight into what the models are suited for and how what you’re asking the model to do lines up with what that model is suited for, and it is not always 100% clear, he added.Related:Anthropic maintains its focus on safety in IPO filingMoreover, for both OpenAI and Anthropic, the race to lower model prices could have distinct consequences, especially as both companies pursue public listings, Nicholson said. Price reductions could lead investors to think the technology is less valuable, or it could indicate greater demand and, therefore, greater profitability.“It remains to be seen,” Nicholson said.Other than reducing the price, OpenAI said GPT-6.1 Terra also has a latency advantage over its Astra and Sol models on some tasks. This means it can accelerate more agentic, high-volume enterprise workflows, said Arun Chandrasekaran, an analyst at Gartner. However, speeding up enterprise workflows requires greater caution, he said.“Greater autonomy also increases operational and security risks, making model routing, task-level ROI, access controls, and human oversight essential to scaling adoption safely,” Chandrasekaran added.Esther Shittu is a TechTarget news writer and podcast producer and host covering AI technology.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.