Run Llama-Nemotron Super 49B on-premises
○ Memory-fit arithmetic — checkable math, not a benchmark
Llama-Nemotron Super 49B is NVIDIA's reasoning- and tool-calling-tuned model, NAS-compressed specifically to run well on a single accelerator. On a machine with 128 GB of memory it fits with plenty of headroom.
Here is the arithmetic against a machine with 128 GB of memory.
Memory fit in 128 GB
| Parameters | 49B (dense, NAS-compressed) |
|---|---|
| 4-bit weights | ~28 GB |
| Reference memory | 128 GB (one machine) |
| Left for context + other models | roughly 90 GB |
| Fits in 128 GB | yes |
The model was compressed to fit a single accelerator, so a 128 GB machine runs it with large context headroom to spare.
What it serves well
- Reasoning, RAG, and tool-calling workloads on NVIDIA hardware.
- Setups that want NVIDIA-native tuning and ecosystem alignment.
- Leaving memory free to co-host embedding and coder models.
Honest limits
- Memory arithmetic, not a benchmark.
- It ships under the NVIDIA Open Model License (with Llama 3.3 community terms); we review licensing fit in the assessment.
- The larger Nemotron Ultra (~253B) does not comfortably fit in 128 GB of memory.
Frequently asked questions
Does Super 49B fit in 128 GB of memory?
Yes, comfortably — ~28 GB at 4-bit against 128 GB leaves roughly 90 GB for context and other models.
Why does it fit so easily?
It was NAS-compressed by NVIDIA to run on a single accelerator, so its footprint is small relative to its capability.
License?
NVIDIA Open Model License with Llama 3.3 community terms; we confirm fit for your use in the assessment.
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