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
- 2025-07-06
- 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 |
|---|---|---|---|---|---|
| BF16 | 16.00 | 112.2 GB | — | 102.00 GB | Brain floating point 16 — preferred for training |
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 GB5 devices with unified memory can run Llama 3 1 Nemotron 51B Instruct, including NVIDIA DGX H100, NVIDIA DGX A100 640GB, Mac Studio M4 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 ~26 tok/s on AMD Instinct MI300X. Speed depends mainly on GPU memory bandwidth. Real-world results typically within ±20%.
tok/s = (bandwidth GB/s ÷ model GB) × efficiency
Example: AMD Instinct MI300X → 5300 ÷ 112.2 × 0.55 = ~26 tok/s
Estimated speed at BF16 (112.2 GB)
~26 tok/s~16 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?
5 devices with unified memory can run Llama 3 1 Nemotron 51B Instruct at BF16 (112.2 GB), including Mac Pro M2 Ultra (192 GB), Mac Studio M2 Ultra (192 GB), Mac Studio M4 Max (128 GB), NVIDIA DGX A100 640GB. Apple Silicon Macs use unified memory shared between CPU and GPU, making them well-suited for local LLM inference.