AI Model Running Costs Fall to Yearly Low Amid Global Price War
Average inference prices dropped to between US$1.16 and US$1.18 per million tokens, driven by Chinese open-source tools like DeepSeek.
Quick Look
The cost for businesses to run AI models hit a yearly low between US$1.16 and US$1.18 per million tokens, driven by a global price war and Chinese open-source tools like DeepSeek, according to Jefferies and Silicon Data.
AI-generated summary
Why It Matters
Global price competition and open-source models are altering the economics of artificial intelligence deployment.
The cost for businesses to run AI models has fallen to a yearly low, according to research by investment bank Jefferies, driven by a heated global price war and a surge in adoption of low-cost Chinese open-source tools, such as those from DeepSeek.
Average inference prices – measured per million tokens, or chunks of data handled by a model – ranged between US$1.16 and US$1.18 from August 6 to 8. That marked the lowest level recorded this year, Jefferies said on Monday, citing data from US research firm Silicon Data. Average unit costs have plummeted from US$2.04 on May 31 and US$1.45 in late July.
Silicon Data’s index tracks pricing across business application programming interface (API) providers and open-weight inference platforms used by software developers.
The price decline coincided with an “increasing emphasis on cost efficiencies” across both the US and Chinese tech ecosystems, Jefferies analysts led by Thomas Chong noted.
On the open-source front, Chinese firms are pushing the boundaries of affordable computing.
Open Questions
- How will US competitors respond to lower Chinese AI inference prices?
- Will profit margins for API providers shrink further?
