NVIDIA H100 / H200

The H100 (Hopper) and H200 are NVIDIA's data-center AI accelerators. Closed silicon, closed ISA (PTX as the published intermediate, SASS as the actual hardware ISA), tightly bound to the CUDA software ecosystem. The H100 ships with 80GB of HBM3 memory; the H200 was refreshed with 141GB of HBM3e and higher bandwidth. Why it dominates: not just the hardware. The CUDA software stack (cuDNN, cuBLAS, NCCL, TensorRT-LLM) has compounded developer attention for fifteen years. Every framework, every inference engine, every research codebase assumes CUDA as the default backend. The competing accelerators (AMD MI300X, Tenstorrent, Intel Gaudi) lag by years on per-framework optimization not because the hardware is worse on paper, but because the kernels have not been written. This is the lock-in pattern named in the silicon-defeats-open-weights argument. Production-ready as the de facto frontier accelerator. The vast majority of frontier training runs in 2024-2026 used H100s or H200s; subsequent Blackwell-series accelerators (B100/B200) are shipping but H100/H200 remain the workhorse fleet. Available via every major hyperscaler and dedicated AI clouds (CoreWeave, Lambda, etc.). Street price typically $25-40K for an H100; not sold to individuals at scale.