Companies are shifting from "tokenmaxxing"—where employees competed to use the most AI tokens—to "modelmaxxing," which routes tasks to the most efficient and cost-effective model. "The AI race is no longer just about building the best model," said Soumen Mandal, principal analyst at Counterpoint Research, adding that "the right balance of capability, cost and deployment flexibility will ultimately determine the winners in the AI market." Chinese AI companies are offering capable models for a fraction of the cost of US rivals. This month, Chinese AI firm Moonshot launched Kimi K3, a model that outperformed all rivals except Anthropic’s Claude Fable 5 and OpenAI’s GPT-5.6, just before Alibaba previewed its Qwen3.8 Max model. In June, Coinbase CEO Brian Armstrong explained how to keep AI spend flat while token usage grows, including by better routing. "This is the first year where AI spend has been a big topic," OpenAI CEO Sam Altman told CNBC. An IDC survey shows that 47% of 260 US decision-makers at companies with more than 1,000 employees reported using made-in-China models for at least one use case, and 20% reported extensive use. In a separate survey from late last year of roughly 100 respondents, 73% reported using or testing AI-driven routing, and 72% reported using or testing automated routing based on input or metadata analysis