CUDA is becoming more critical, not less, every day. Software developed around CUDA is vastly outpacing what other companies produce. And saving a few millions when creating new models doesn't matter; NVIDIA is pretty efficient at scale.

I don't know if you've heard, but NVIDIA is about to add a monthly payment for additional CUDA features and I'm almost certain that many big companies will be happy to pay for them.

> But most models will run or retrain fine now without CUDA.

This is correct for some small startups, not big companies.

CUDA is incredibly important still. It's still an incredible amount of work to get packages working on multiple GPU paradigms, and by default everyone still starts with CUDA.

The example I always give is FFT libraries - if you compare cuFFT to rocFFT. rocFFT only just released support for distributed transforms in December 2024, something you've been able to do since CUDA Toolkit v8.0, released in 2017. It's like this across the whole AMD toolkit, they're so far behind CUDA it's kind of laughable.