H200 vs multi-GPU RTX PRO 6000 Blackwell: how to pick inference hardware by budget
recentheartbroken · reddit · 2026-10-07
A hands-on comparison for building an inference server on equal budgets. RTX PRO 6000: 96GB GDDR7 at 1.792 TB/s, native FP4, no NVLink; H200: 141GB HBM3e at 4.8 TB/s with NVLink, FP8 minimum.
- PRO 6000 wins: single/small multi-card inference up to 70B at sensible quantization, much cheaper per card, manageable power, far better availability, native FP4 helps 4-bit models.
- H200 wins: bandwidth-bound workloads — long-context serving, big models you can't shard over PCIe, and tensor parallelism where NVLink matters.
Key caveat: decode is usually memory-bandwidth-bound, not compute-bound, so datasheet TFLOPS says almost nothing about tokens/sec.
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