GLM 5.2 and the coming AI margin collapse
The article argues that the AI industry's profitability depends more on inference costs than training costs. It highlights the emergence of high-quality open-weights models like GLM 5.2 as a potential disruptor to the margins of major AI labs.
Why it matters
This analysis challenges the market narrative that training costs are the primary financial hurdle for AI companies, shifting focus to the long-term economics of model inference.
What feels like decades ago, markets recoiled at DeepSeek's R1 model. The theory being that given the underlying V3 model reportedly cost under $6m to train, the market therefore thought the huge investment in capex for model training was over, and thus the stock price of Nvidia et al collapsed overnight .
The author provides a financial analysis of the AI market, though it relies on personal 'napkin math' and industry speculation.
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