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Text model · Nemotron

NE Llama-3.3-Nemotron-Super-49B-v1: RAM and VRAM requirements

Llama-3.3-Nemotron-Super-49B-v1 needs about 30.6 GB to run at Q4_K_M (the Q4_K_M GGUF file is ~28.14 GB to download; KV cache and overhead add the rest), or about 51.9 GB at Q8_0. The lightest hardware that runs it is Nvidia GeForce RTX 5090 (32GB).

Nemotron family · 49B params · released Mar 2025.

Shopping for hardware? See what runs Llama-3.3-Nemotron-Super-49B-v1 →

License NVIDIA Open Model License + Llama 3.3 Community License · Conditional ↓ 182.7K/mo ♥ 325 on HuggingFace
Q4_K_M GGUF
28.14 GB
Q8_0 GGUF
49.36 GB
Memory @ Q4 (4k)
~30.6 GB
Context
128 k

Q4_K_M and Q8_0 are GGUF download (file) sizes. Memory @ Q4 includes the KV cache and overhead, so it runs larger than the file on disk.

Will it run on your device?

Llama-3.3-Nemotron-Super-49B-v1 runs on 8 of 40 tracked devices at Q4_K_M.

5 run well 3 tight fit 32 too small
Fit check Q4_K_M
No, not enough memory
needs 30.6 GB usable 10.5 GB
See the full breakdown

Memory breakdown

Weights (Q4_K_M)28.14 GB
+
KV cache (4k)1.7 GB
+
Overhead0.8 GB
=
Total30.6 GB

How context length changes it

4k context ~30.6 GB 32k context ~42.3 GB 128k context ~82.7 GB

Longer context grows the KV cache quickly: Llama-3.3-Nemotron-Super-49B-v1 needs ~30.6 GB at 4k but ~82.7 GB at 128k, which can push it past a device that fits it at a short context.

Speed drops too: every token re-reads the KV cache, so at 128k context Llama-3.3-Nemotron-Super-49B-v1 generates at roughly ~34% of its short-context speed. How this is estimated.

Quantization sizes

GGUF quantson disk
Quantization Size on disk
Q2_K 20.5 GB est
Q3_K_M 23.9 GB est
Q4_K_M (default) 28.14 GB
Q5_K_M 34.9 GB est
Q6_K 40.2 GB est
Q8_0 49.36 GB
FP16 99.74 GB

Lower quant = smaller and faster, slightly lower quality. Q4_K_M is the common default.

Run it

llama.cpp
$ llama-cli -hf bartowski/nvidia_Llama-3_3-Nemotron-Super-49B-v1-GGUF:Q4_K_M
LM Studio
$ lms get bartowski/nvidia_Llama-3_3-Nemotron-Super-49B-v1-GGUF

Which devices can run Llama-3.3-Nemotron-Super-49B-v1?

Apple Silicon Macs

RAM-only laptops

iPhone & iPad

Android

NVIDIA GPUs

AMD GPUs

Same job, different size

Pick by what fits your memory: step down to free up VRAM, or step up if you have headroom.

Next size down Mixtral 8x7B 46.7B Next size up Llama 3.3 70B 70B

Similar models

Head-to-head

FAQ

How much VRAM or RAM does Llama-3.3-Nemotron-Super-49B-v1 need?

At Q4_K_M, Llama-3.3-Nemotron-Super-49B-v1 needs about 30.6 GB (weights ~28.14 GB + KV cache + overhead) at a 4k context. At Q8_0 budget ~51.9 GB.

What is the Q4_K_M GGUF file size of Llama-3.3-Nemotron-Super-49B-v1?

The Q4_K_M GGUF file is about 28.14 GB to download, and the Q8_0 GGUF is about 49.36 GB. That is the weights file on disk; to run it you also need room for the KV cache and overhead, so budget ~30.6 GB of memory at Q4_K_M.

Can Llama-3.3-Nemotron-Super-49B-v1 run on a laptop?

Llama-3.3-Nemotron-Super-49B-v1 is large; you need a high-memory Mac or multi-GPU setup at Q4_K_M.

Can I use Llama-3.3-Nemotron-Super-49B-v1 commercially?

Conditionally. NVIDIA Open Model + Llama 3.3 Community License; check the terms for commercial use.

Understand the numbers

Short guides to the ideas behind Llama-3.3-Nemotron-Super-49B-v1's memory and quant figures.

NVIDIA's reasoning-tuned Llama 3.3 derivative. 49B dense; fits a 32GB+ GPU or a high-memory Mac at Q4.

Sources

Last validated 2026-08-03. Memory figures are estimates. See methodology.