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Running Nemotron 3 Ultra on RTX PRO 6000 server

Nemotron 3 Ultra has 550 billion parameters. RTX PRO 6000 server offers 768 GB of GDDR7 across 8 GPUs memory. This page puts the two side by side.

Short answer. Nemotron 3 Ultra fits comfortably on RTX PRO 6000 server. In FP8, its weights take about 632 GB of the 768 GB available, leaving 136 GB for the attention cache and concurrency.

How much memory does Nemotron 3 Ultra need?

Weights take the parameter count multiplied by the format size, plus a 15% runtime margin for activations and buffers. The attention cache sits on top: it grows with context length and with the number of concurrent requests, so it is sized case by case.

FormatWeights in memory On this machineWhat the format costs
FP161,265 GBdoes not fitfull precision, the quality reference
FP8632 GBtightnegligible loss on most tasks
NVFP4316 GBfitsBlackwell format, native FP4 compute
Q4316 GBfitsblock quantisation, broadly supported

Nemotron 3 Ultra activates 55 billion parameters per token out of 550 billion. Active parameters govern speed, not footprint: every expert stays resident in memory. Confusing the two under-sizes the machine by an order of magnitude.

What is left to serve requests?

Nemotron 3 Ultra fits comfortably on RTX PRO 6000 server. In FP8, its weights take about 632 GB of the 768 GB available, leaving 136 GB for the attention cache and concurrency. The remaining margin decides how many concurrent requests and how much context the machine sustains. A margin below a quarter of memory forces a limit on context or on concurrency.

RTX PRO 6000 server ranges from 250 to 350 k€, indicative and not contractual. The machine targets the PME, GE segment.

Where else can Nemotron 3 Ultra run?

See the Nemotron 3 Ultra and RTX PRO 6000 server fact sheets.

How much memory does Nemotron 3 Ultra need?

In FP8, weights take about 632 GB including the runtime margin. The attention cache sits on top and depends on context.

Does Nemotron 3 Ultra fit on RTX PRO 6000 server?

Nemotron 3 Ultra fits comfortably on RTX PRO 6000 server. In FP8, its weights take about 632 GB of the 768 GB available, leaving 136 GB for the attention cache and concurrency.

Method

Parameter counts and memory figures come from the site fact sheets. Memory footprints are calculated, not measured: a reading on real hardware may differ depending on the engine and the exact weight format. Prices are indicative and not contractual.