Coinbase CEO Brian Armstrong revealed that to reduce costs in AI usage, they are directing queries to cheaper models. Armstrong noted that this approach keeps expenses roughly stable in some cases while maintaining efficiency despite a rapid increase in token usage.
He emphasized that although the newest models offer powerful features, they consume more tokens. According to him, users turn to these models only when the highest level of cognitive power is required.
The CEO predicted that within the next 12 to 18 months, 80% of workloads will run on models that are 99% cheaper. Armstrong believes the most advanced models will be used mainly in specialized areas such as scientific breakthroughs and managing AI agents.
In Armstrong’s assessment, the limiting factor in AI will increasingly be energy and processing power rather than better models. This approach marks a departure from the long-standing tech industry mindset of "use more tokens."
The statement caught the attention of some tech figures. Marc Andreessen described the approach as interesting, while Hugging Face co-founder Julien Chaumond noted that model redirection has recently grown rapidly.
Box CEO Aaron Levie found Armstrong’s figures somewhat extreme but said AI usage will differentiate into high-level and high-volume tasks in the coming years. Harvey co-founder Winston Weinberg also highlighted that "intelligence allocation" will become very important in AI.
While the tech community previously favored approaches emphasizing higher token usage, a cost-focused perspective has gained strength recently. Around Y Combinator, entrepreneurs have been encouraged to be relaxed about tokens, with some founders arguing that cutting tokens is unnecessary.
Glean co-founder Tony Gentilcore agreed with Armstrong’s view. Gentilcore said technical circles already understand this picture, and the real uncertainty lies in financial markets assuming Opus prices on an infinite scale.
