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H100 vs RTX Pro 6000 Blackwell for local AI

Both fit the same models we track, up to gpt-oss 120B. The H100 generates about 87% faster on any model both can run, because it has 3350 GB/s of memory bandwidth to the RTX Pro 6000 Blackwell's 1792 GB/s.

The numbers that matter

Memory and bandwidth

Memory decides which models fit. Bandwidth decides how fast they generate, because every token reads the model's active weights once.

H100RTX Pro 6000 Blackwell
Memory80 GB VRAM96 GB VRAM
Bandwidth3350 GB/s1792 GB/s
Biggest model that fitsgpt-oss 120Bgpt-oss 120B
Best everyday pickgpt-oss 120B, ~400 tok/sgpt-oss 120B, ~220 tok/s
Model by model

Every model, side by side

Estimated generation speed at the largest memory size each was sold in (80 GB and 96 GB).

ModelH100RTX Pro 6000 Blackwell
Qwen3 4B
About 4 GB
~740 tok/s Runs great~390 tok/s Runs great
Qwen3 8B
About 7 GB
~350 tok/s Runs great~190 tok/s Runs great
Gemma 3 12B
About 10 GB
~230 tok/s Runs great~120 tok/s Runs great
Qwen3 14B
About 11 GB
~200 tok/s Runs great~110 tok/s Runs great
gpt-oss 20B
About 16 GB
~590 tok/s Runs great~310 tok/s Runs great
Gemma 3 27B
About 19 GB
~110 tok/s Runs great~58 tok/s Runs great
Qwen3 30B-A3B
About 21 GB
~590 tok/s Runs great~310 tok/s Runs great
Qwen3 32B
About 22 GB
~92 tok/s Runs great~49 tok/s Runs great
Llama 3.3 70B
About 45 GB
~43 tok/s Runs great~23 tok/s Usable
gpt-oss 120B
About 67 GB
~400 tok/s Runs great~220 tok/s Runs great
Qwen3 235B-A22B
About 144 GB
Needs 144 GBNeeds 144 GB
DeepSeek R1 671B
About 406 GB
Needs 406 GBNeeds 406 GB
Which should you get?

The H100, for speed. They fit the same models. Price matters as much as either number: check used prices on the builds page, where every parts list has a measured or estimated speed.

How we estimate

Both columns use the same formula: memory bandwidth divided by the weights read per token, calibrated on our own rack, with Ollama's default 4-bit sizes. Real results are usually within about a third. Measured either one? Send us the number.

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