July 30 (Reuters) – OpenAI slashed prices of its low- and mid-tier AI models on Thursday, a move that may intensify competition in the industry as U.S. companies battle cheaper Chinese rivals for customers increasingly wary of the technology’s ballooning costs.
The ChatGPT maker lowered the cost of its smaller GPT-5.6 Luna model by 80% and its mid-tier Terra by 20%, while leaving the price of its biggest and flagship Sol model unchanged.
The cuts show that rising cost scrutiny by businesses facing hefty AI bills is forcing American labs to rethink pricing. Many tech CEOs have also said in recent months that cheaper AI options are key to the technology’s widespread adoption.
OpenAI’s new pricing also turns up the heat on Anthropic, whose Claude models dominate enterprise and developer use but sit at the costlier end of the market. Both companies have been under pressure from open-source Chinese rivals such as Z.ai’s GLM-5.2 that nearly match their performance at a lower cost.
Analysts have said that cutting prices could boost usage of OpenAI’s and Anthropic’s technology, but strain their finances ahead of highly anticipated initial public offerings.
While Thursday’s cuts affect only OpenAI’s smaller and mid-tier models, the company said it would still benefit businesses broadly as those models can now do work that recently required a top-tier system at far lower cost.
The new pricing means businesses using OpenAI’s technology will have to pay less for every million “tokens”, or the units used to measure AI usage, they run through the models.
Sending text to Luna drops to 20 cents per million tokens from $1 and Terra’s to $2 from $2.50, while generating responses falls to $1.20 and $12 from $6 and $15, respectively.
Anthropic’s mid-tier Claude Sonnet 4.6 model, meanwhile, costs $3 per million input tokens and $15 per million output tokens, above the rates for Terra.
OpenAI said the lower prices were partly enabled by efficiency gains from GPT-5.6, including the model’s ability to improve code and optimize performance during internal development.
Overall, prices of tokens have been falling in the past year, but the cost of completing a task is rising as AI firms shift from flat subscriptions to usage-based pricing.
That is leaving companies with unpredictable and often higher bills as usage per task becomes harder to estimate.
(Reporting by Aditya Soni in Bengaluru and Deepa Seetharaman in San Francisco; Editing by Devika Syamnath)
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