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Models are going to end up priced as a commodity (we’re already seeing this happen). It will be profitable but not have the large margins that are historically true for software. From a financial perspective models look a lot more like a hardware product than a software product. 1/

Ted Underwood@tedunderwood.com

Alternate hypothesis: Kimi K3 and Qwen 3.8 show that leading in model releases does not esp. matter commercially. MSFT and GOOG may well have figured out that what will matter is effective agentic integration with the vast user data in their core office suites. That’s hard but worth getting right.

4/8/26, 1:06 pm0 reposts0 likes

Mason Stallmo

@mstallmo.com

4 Aug

There are a two big factors at play here. 1) model output (tokens) are fungible. 2) Training and operating models are VERY hardware intensive. There is a large capex required to get into model development and serving. 2/

Mason Stallmo

@mstallmo.com

4 Aug

Compare this to the energy (oil) industry and there are a lot of similarities. A lot of capex is required to drill and refine oil. There is minimal differentiation in the final product (people don’t care who produces the gas they put in their cars) 3/

Mason Stallmo

@mstallmo.com

4 Aug

If you’re looking for traditional software margins the value is in the software that integrates AI into products and workflows. This is where products will be stickier and the capex will be in line with capex for traditional software products. This might be MSFT and Google’s play. 4/4