Timteh673 BF16 49B Parameters

VRAM Requirements for
Nemotron-Super-49B-v1.5-Uncensored-GGUF BF16

To run Nemotron-Super-49B-v1.5-Uncensored-GGUF locally at BF16 quantization, you need at minimum 100.8 GB of GPU VRAM.

100.8 GB
Required VRAM
98 GB
File Size
8K tokens
Context Window
49B
Parameters
Estimated VRAM Required
100.8
GB
Cluster Required
0 16GB
RTX 3080 48GB
A6000 80GB+

Recommended GPU Configurations

Budget $40,000+

4× A100 40GB Cluster

160 GB

Distributed inference across 4 A100s. Minimum viable cluster.

Balanced $60,000+

2× H100 80GB NVLink

160 GB HBM3

NVLink bridge enables unified 160GB VRAM pool.

Ultimate $3,000,000+

NVIDIA GB200 NVL72

1.4 TB HBM3e

Next-gen Grace Blackwell Superchip. Built for frontier models.

📊 VRAM Calculation Breakdown

Model File Size (BF16) 98 GB
Context Overhead (8,192 tokens × 49B × 2 ÷ 1M) 0.803 GB
System Buffer (OS + CUDA runtime) 2.00 GB
Total Required VRAM 100.8 GB

Try a Different Quantization

Use the interactive calculator to compare Nemotron-Super-49B-v1.5-Uncensored-GGUF across all available formats.

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Nemotron-Super-49B-v1.5-Uncensored-GGUF — Other Quantizations

Q2_K 15.31 GB file
18.11 GB
Q3_K_M 21.44 GB file
24.24 GB
Q4_K_M 27.56 GB file
30.36 GB
Q5_K_M 33.69 GB file
36.49 GB
Q6_K 39.81 GB file
42.61 GB
Q8_0 52.06 GB file
54.86 GB
BF16 Current
100.8 GB
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Frequently Asked Questions

Can I run Nemotron-Super-49B-v1.5-Uncensored-GGUF BF16 on a consumer GPU?
Running Nemotron-Super-49B-v1.5-Uncensored-GGUF BF16 locally requires 100.8 GB VRAM, which exceeds consumer GPUs. You'll need prosumer cards like the NVIDIA A6000 (48GB) or an A100 (80GB).
What happens if I don't have enough VRAM?
If your GPU VRAM is insufficient, llama.cpp and similar tools will offload model layers to system RAM (CPU inference). This is much slower — expect 10-50× the generation latency compared to full GPU inference.
Can I use multiple GPUs to run Nemotron-Super-49B-v1.5-Uncensored-GGUF?
Yes! Tools like llama.cpp, vLLM, and Ollama support tensor parallelism across multiple GPUs. For example, 2× RTX 3090 (24GB each) gives you 48GB total VRAM, which can run many large models.
Is BF16 quality good enough for production?
FP16/BF16 is the standard precision used for production inference and serves as the quality baseline. All fine-tuned models are typically served at this precision.