> the GPU could be used to encode h264, and apparently yes, but it's not really worth it compared to CPU.

It depends on what you're going for. If you're trying to do the absolute highest fidelity for archiving a blu-ray disk, AMD Epyc reigns supreme. That's because you need a lot of flexibility to really dial in the quality settings. Pirates over at PassThePopcorn obsess over minute differences in quality that I absolutely cannot notice with my eyes, and I'm glad they do! Their encodings look gorgeous. This quality can't be achieved with the silicon of hardware-accelerated encoders, and due to driver limitations (not silicon limitations) also cannot be achieved by CUDA cores / execution engines / etc on GPUs.

But if you're okay with a small amount of quality loss, the optimum move for highest # of simultaneous encodes or fastest FPS encoding is to skip the CPU and GPU "general compute" entirely - going with hardware accelerated encoding can get you 8-30 1080p simultaneous encodes on a very cheap intel iGPU using QSV/VAAPI encoding. This means using special sections of silicon whose sole purpose is to perform H264/H265/etc encoding, or cropping / scaling / color adjustments ... the "hardware accelerators" I'm talking about are generally present in the CPU/iGPU/GPU/SOC, but are not general purpose - they can't be used for CUDA/ROCm/etc. Either they're being used for your video pipeline specifically, or they're not being used at all.

I'm doing this now for my startup and we've tuned it so it uses 0% of the CPU and 0% of the Render/3D engine of the iGPU (which is the most "general purpose" section of the GPU, leaving those completely free for ML models) and only utilizing the Video Engine and Video Enhance engines.

For something like Frigate NVR, that's perfect. You can support a large # of cameras on cheap hardware and your encoding/streaming tasks don't load any silicon used for YOLO, other than adding to overall thermal limits.

Video encoding is a very deep topic. You need to have benchmarks, you need to understand not just "CPU vs GPU" ... but down to which parts of the GPU you're using. There's an incredible amount of optimization you can do for your specific task if you take the time to truly understand the systems level of your video pipeline.