When Topaz Video Enhance AI (VEAI) launched in February, 2020, it only supported NVIDIA GPUs on Windows. If you had an AMD GPU, you were limited to CPU-only processing, which was painfully slow and impractical for most users.
You can see my own old post from back then, where I was pleading with Topaz to add AMD GPU support:
AMD GPU support was finally added starting with version 1.7.0, released in November 2020. Here’s the official release notes thread, which clearly mentions the new AMD compatibility:
However, it didn’t take long for me to realize that relying on an AMD GPU for AI-specific tasks was a shortsighted choice. The vast majority of AI software—especially open-source projects on GitHub—relies on CUDA, leaving AMD users with workarounds or dead ends.
NVIDIA’s dominance extends beyond hardware. The company frequently dispatches engineers to partners and projects at no cost, helping them optimize software for its GPUs. In stark contrast, AMD often ignores outreach efforts. Ultimately, this relentless ecosystem-building has cemented CUDA as the de facto industry standard, leaving AMD far behind.
