Llama 3 3 Nemotron Super 49B V1 5 GGUF — Hardware Requirements & GPU Compatibility
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72 downloads
1 likesSpecifications
- Publisher
- mradermacher
- Family
- Llama 3
- Parameters
- 49B
- License
- Other
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How Much VRAM Does Llama 3 3 Nemotron Super 49B V1 5 GGUF Need?
Select a quantization to see compatible GPUs below.
| Quantization | Bits | VRAM | + Context | File Size | Quality |
|---|---|---|---|---|---|
| BF16 | 16.00 | 107.8 GB | — | 98.00 GB | Brain floating point 16 — preferred for training |
Which GPUs Can Run Llama 3 3 Nemotron Super 49B V1 5 GGUF?
BF16 · 107.8 GBLlama 3 3 Nemotron Super 49B V1 5 GGUF (BF16) requires 107.8 GB of VRAM to load the model weights. For comfortable inference with headroom for KV cache and system overhead, 141+ GB is recommended. No single GPU has enough memory — multi-GPU or cluster setups are needed.
Which Devices Can Run Llama 3 3 Nemotron Super 49B V1 5 GGUF?
BF16 · 107.8 GB5 devices with unified memory can run Llama 3 3 Nemotron Super 49B V1 5 GGUF, 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 3 Nemotron Super 49B V1 5 GGUF need?
Llama 3 3 Nemotron Super 49B V1 5 GGUF requires 107.8 GB of VRAM at BF16.
VRAM = Weights + KV Cache + Overhead
Weights = 49B × 16 bits ÷ 8 = 98 GB
KV Cache + Overhead ≈ 9.8 GB (at 2K context + ~0.3 GB framework)
VRAM usage by quantization
BF16107.8 GB- Can NVIDIA GeForce RTX 5090 run Llama 3 3 Nemotron Super 49B V1 5 GGUF?
No — Llama 3 3 Nemotron Super 49B V1 5 GGUF requires at least 107.8 GB at BF16, which exceeds the NVIDIA GeForce RTX 5090's 32 GB of VRAM.
- Can I run Llama 3 3 Nemotron Super 49B V1 5 GGUF on a Mac?
Llama 3 3 Nemotron Super 49B V1 5 GGUF requires at least 107.8 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 3 Nemotron Super 49B V1 5 GGUF locally?
Yes — Llama 3 3 Nemotron Super 49B V1 5 GGUF can run locally on consumer hardware. At BF16 quantization it needs 107.8 GB of VRAM. Popular tools include Ollama, LM Studio, and llama.cpp.
- How fast is Llama 3 3 Nemotron Super 49B V1 5 GGUF?
At BF16, Llama 3 3 Nemotron Super 49B V1 5 GGUF can reach ~27 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 ÷ 107.8 × 0.55 = ~27 tok/s
Estimated speed at BF16 (107.8 GB)
AMD Instinct MI300X~27 tok/sAMD Instinct MI250X~17 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 3 Nemotron Super 49B V1 5 GGUF?
At BF16, the download is about 98.00 GB.
- Which GPUs can run Llama 3 3 Nemotron Super 49B V1 5 GGUF?
No single consumer GPU has enough VRAM to run Llama 3 3 Nemotron Super 49B V1 5 GGUF at BF16 (107.8 GB). Multi-GPU or professional hardware is required.
- Which devices can run Llama 3 3 Nemotron Super 49B V1 5 GGUF?
5 devices with unified memory can run Llama 3 3 Nemotron Super 49B V1 5 GGUF at BF16 (107.8 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.