Llama 3 1 Nemotron 51B Instruct — Hardware Requirements & GPU Compatibility
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Llama 3 1 Nemotron 51B Instruct is a 51B-parameter open language model from NVIDIA in the Llama 3 family. It supports a context window of up to 131,072 tokens. At BF16 it needs about 112.20 GB of VRAM — see which GPUs and Macs can run it below.
570 downloads
209 likesSpecifications
- Publisher
- NVIDIA
- Family
- Llama 3
- Parameters
- 51B
- Architecture
- DeciLMForCausalLM
- Context Length
- 131,072 tokens
- Vocabulary Size
- 128,256
- Release Date
- 2024-09-22
- License
- Other
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HuggingFace
How Much VRAM Does Llama 3 1 Nemotron 51B Instruct Need?
Select a quantization to see compatible GPUs below.
| Quantization | Bits | VRAM | + Context | File Size | Quality |
|---|---|---|---|---|---|
| BF16est. | 16.00 | 112.2 GB | — | 102.00 GB | Brain floating point 16 — preferred for training |
est.= calculated VRAM estimate; no published GGUF file found for that quantization yet. Other rows are verified against real community uploads.
Which GPUs Can Run Llama 3 1 Nemotron 51B Instruct?
BF16 · 112.2 GBLlama 3 1 Nemotron 51B Instruct (BF16) requires 112.2 GB of VRAM to load the model weights. For comfortable inference with headroom for KV cache and system overhead, 146+ GB is recommended. No single GPU has enough memory — multi-GPU or cluster setups are needed.
Which Devices Can Run Llama 3 1 Nemotron 51B Instruct?
BF16 · 112.2 GB10 devices with unified memory can run Llama 3 1 Nemotron 51B Instruct, including NVIDIA DGX H100, NVIDIA DGX A100 640GB, MacBook Pro 16" M5 Max (128 GB).
Runs great
— Plenty of headroom
Decent
— Enough memory, may be tightRelated Models
Frequently Asked Questions
- How much VRAM does Llama 3 1 Nemotron 51B Instruct need?
Llama 3 1 Nemotron 51B Instruct requires 112.2 GB of VRAM at BF16.
VRAM = Weights + KV Cache + Overhead
Weights = 51B × 16 bits ÷ 8 = 102 GB
KV Cache + Overhead ≈ 10.2 GB (at 2K context + ~0.3 GB framework)
VRAM usage by quantization
BF16112.2 GB- Can NVIDIA GeForce RTX 5090 run Llama 3 1 Nemotron 51B Instruct?
No — Llama 3 1 Nemotron 51B Instruct requires at least 112.2 GB at BF16, which exceeds the NVIDIA GeForce RTX 5090's 32 GB of VRAM.
- Can I run Llama 3 1 Nemotron 51B Instruct on a Mac?
Llama 3 1 Nemotron 51B Instruct requires at least 112.2 GB at BF16, which exceeds the unified memory of most consumer Macs. You would need a Mac Studio or Mac Pro with a high-memory configuration.
- Can I run Llama 3 1 Nemotron 51B Instruct locally?
Yes — Llama 3 1 Nemotron 51B Instruct can run locally on consumer hardware. At BF16 quantization it needs 112.2 GB of VRAM. Popular tools include Ollama, LM Studio, and llama.cpp.
- How fast is Llama 3 1 Nemotron 51B Instruct?
At BF16, Llama 3 1 Nemotron 51B Instruct can reach ~39 tok/s on AMD Instinct MI350X. Speed depends mainly on GPU memory bandwidth. Real-world results typically within ±20%.
tok/s = (bandwidth GB/s ÷ model GB) × efficiency
Example: NVIDIA B200 → 8000 ÷ 112.2 × 0.65 = ~46 tok/s
Estimated speed at BF16 (112.2 GB)
~46 tok/s~46 tok/s~39 tok/sReal-world results typically within ±20%. Speed depends on batch size, quantization kernel, and software stack.
- What's the download size of Llama 3 1 Nemotron 51B Instruct?
At BF16, the download is about 102.00 GB.
- Which GPUs can run Llama 3 1 Nemotron 51B Instruct?
No single consumer GPU has enough VRAM to run Llama 3 1 Nemotron 51B Instruct at BF16 (112.2 GB). Multi-GPU or professional hardware is required.
- Which devices can run Llama 3 1 Nemotron 51B Instruct?
18 devices with unified memory can run Llama 3 1 Nemotron 51B Instruct at BF16 (112.2 GB), including ASUS Ascent GX10, Asus ROG Flow Z13 (2025, Ryzen AI Max+ 395, 128 GB), Beelink GTR9 Pro (Ryzen AI Max+ 395, 128 GB), Framework Desktop (Ryzen AI Max+ 395, 128 GB). Apple Silicon Macs use unified memory shared between CPU and GPU, making them well-suited for local LLM inference.