NVidia has enormous operating margins, so a competitive solution doesn't have to match or beat NVidia's scale efficiencies; it just has to beat delivered cost.

One objective of the project might be simply to provide credible negotiating leverage when dealing with existing suppliers like NVidia. You don't have to deploy at scale for that to work, but you do have to look like you could if pushed hard enough.

In the short and medium term, it probably won't be more economical to produce for OpenAI. Where OpenAI is benefitting from their own chip is being able to tailor it to their models and workloads. When you buy off the shelf Nvidia, its not perfectly tailored and OpenAI has to spend marginally more to run off that chip. At the scale OpenAI is operating at and plans to operate at, that margin becomes pretty big $$

Because it's actually Broadcom that is doing most of the work.

By leveraging the experience Broadcom has in this area. Still remains to be seen how that goes when they want to scale production.

"How can OpenAI produce a LLM at scale more economically than Google, Amazon, and Microsoft which have experience in planet scale software and scale efficiencies unlike them".

One answer is they're quite good at poaching talent.

Replace OpenAI with Apple and Nvidia with Intel.