Quick comparison of AMD and Nvidia GPU's for LLM work
Quick comparison why Nvidia is preferred over its (only) competitor AMD for LLM work. Aspect NVIDIA GPUs AMD Radeon Pro Framework Support Extensive support via CUDA for PyTorch, TensorFlow, and most ML frameworks Limited support, fewer frameworks optimized for AMD ML Ecosystem Mature CUDA ecosystem with wide adoption Less developed ROCm ecosystem with limited compatibility Software Integration Well-established pipelines and tools More restricted options, may require additional setup Raw Computing Power Strong performance with direct ML optimization Good raw power but harder to leverage for ML tasks Memory Options Various models with sufficient VRAM (16GB+) Competitive VRAM options but harder to utilize for ML Primary Use Case Strong in both ML/AI and professional graphics Better suited for professional graphics work LLM Specific Support De facto standard for LLM deployment Limited practical application for LLMs Towards end of CY24: ...