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Chinese open-weight AI models have turned inference into a commodity, calling into question the sustainability of the frontier labs’ 60%-80% markups. Yet the walls may not be closing in on OpenAI and Anthropic as quickly as benchmarks and public sentiment suggest.
Jesse Zhang, co-founder of Decagon, a maker of customer-service chatbots, recently argued that running open models requires technical finesse many corporations would rather pay to avoid. As the old adage goes, “no one gets fired for buying IBM.” Most enterprises could build the infrastructure in-house, but it's far easier to hand off the problem to Anthropic or OpenAI.
Data from OpenRouter, a single API endpoint that unifies inference providers from both open- and closed-weight models, supports this hypothesis. Since mid-May, open-weight models’ share of token usage has climbed nearly one-third to 75%. However, in terms of estimated dollars spent on the platform, closed-source models still crush open-weights.
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