Anthropic · Nvidia · TechCrunch AI
Why the rise of open source AI isn’t hurting Anthropic
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On Monday, Decagon CEO Jesse Zhang published a provocative new theory, posted under the title “Everyone is wrong about open source AI in the enterprise.” The post grapples with one of the most interesting contradictions of today’s AI economy: More mature AI deployments are switching to lighter models, he says, even at his own company.
Key facts
- OpenRouter doesn’t rank models by total spend, but it registers the average token cost for Opus 4.8 as roughly 23x higher than V4 Flash ($1.37 per million tokens, compared to 6 cents)
- Z.ai, the lab behind the popular GLM-5.2 model, jumped into a respectable fourth place over the same period
- In Zhang’s telling, they aren’t competitors, and open source models’ success isn’t coming at the expense of frontier labs
- Either way, this two-tiered economy of models may become a relatively stable feature of the AI economy
Summary
It’s a new way to think about the relationship between frontier and open source models. As more mature use cases switch to lighter models, new use cases keep arising, and the overall spend on frontier models barely goes down. Zhang doesn’t give much data to support the point, but the data isn’t hard to find. But if you scroll down to overall token spend, you’ll see Anthropic still accounts for more than half of the overall AI spend on the platform.