B300 uses the Blackwell Ultra architecture with 288GB HBM3E per GPU, 8TB/s bandwidth and about 15 PFLOPS NVFP4, favoring large-model inference and long context. H200 uses Hopper with 141GB memory and about 1979 TFLOPS FP8, shares the H100 software stack, and suits mixed training and inference on a tighter budget. Choose B300 for inference-heavy, very large models; choose H200 for training-heavy work that reuses existing H100 experience.