NVIDIA-Nemotron-3-Super-120B-A12B-BF16: hardware requirements

NVIDIA-Nemotron-3-Super-120B-A12B-BF16 needs about 90 GB of memory at Q4 quantization — a 86 GB download plus room for context and overhead. That fits a machine with 128GB RAM.

Parameters
124B
Tier
Needs a workstation
Licence
nvidia-open-model
Released
2026-03-10

This is a mixture-of-experts model. Only a fraction of its 124B parameters are used for each token, so it runs faster than its size suggests — but all of it still has to fit in memory. The speed is that of a small model; the memory requirement is that of a large one. More on this →

Will it run on your machine?

Download sizes by quantization

Lower quantization means a smaller file and less memory, at some cost to quality. Q4_K_M is the usual starting point. What is this?

QuantDownloadRAM @ 4KRAM @ 32KSource
Q4_K_Mrecommended86 GB90 GB92 GBmeasured
Q5_K_M96 GB99 GB102 GBmeasured
Q6_K113 GB117 GB119 GBmeasured
Q8_0131 GB135 GB138 GBestimated
BF16247 GB251 GB253 GBestimated

“Measured” sizes are read from published GGUF files (mradermacher/NVIDIA-Nemotron-3-Super-120B-A12B-BF16-i1-GGUF). “Estimated” sizes are derived from the parameter count and are typically within a few percent. The RAM columns add the context cache and runtime overhead to the download size.

Model card on HuggingFace →API specs & pricing →Verified 2026-09-13Tracked for 12 months after release