Llama 3 3 Nemotron Super 49B V1 — Hardware Requirements & GPU Compatibility
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Llama 3 3 Nemotron Super 49B V1 is a 49.9B-parameter open language model from NVIDIA in the Llama 3 family. It supports a context window of up to 131,072 tokens. At Q4_K_M it needs about 32.91 GB of VRAM — see which GPUs and Macs can run it below.
59.0K downloads
329 likesSpecifications
- Publisher
- NVIDIA
- Family
- Llama 3
- Parameters
- 49.9B
- Architecture
- DeciLMForCausalLM
- Context Length
- 131,072 tokens
- Vocabulary Size
- 128,256
- Release Date
- 2025-03-16
- License
- Other
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HuggingFace
How Much VRAM Does Llama 3 3 Nemotron Super 49B V1 Need?
Select a quantization to see compatible GPUs below.
| Quantization | Bits | VRAM | + Context | File Size | Quality |
|---|---|---|---|---|---|
| Q2_K | 3.40 | 23.3 GB | — | 21.19 GB | 2-bit quantization with K-quant improvements |
| Q3_K_S | 3.50 | 24 GB | — | 21.82 GB | 3-bit small quantization |
| Q3_K_M | 3.90 | 26.7 GB | — | 24.31 GB | 3-bit medium quantization |
| Q4_0 | 4.00 | 27.4 GB | — | 24.93 GB | 4-bit legacy quantization |
| Q4_K_M | 4.80 | 32.9 GB | — | 29.92 GB | 4-bit medium quantization — most popular sweet spot |
| Q5_K_M | 5.70 | 39.1 GB | — | 35.53 GB | 5-bit medium quantization — good quality/size tradeoff |
| Q6_K | 6.60 | 45.3 GB | — | 41.14 GB | 6-bit quantization, very good quality |
| Q8_0 | 8.00 | 54.9 GB | — | 49.87 GB | 8-bit quantization, near-lossless |
Which GPUs Can Run Llama 3 3 Nemotron Super 49B V1?
Q4_K_M · 32.9 GBLlama 3 3 Nemotron Super 49B V1 (Q4_K_M) requires 32.9 GB of VRAM to load the model weights. For comfortable inference with headroom for KV cache and system overhead, 43+ 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?
Q4_K_M · 32.9 GB29 devices with unified memory can run Llama 3 3 Nemotron Super 49B V1, including NVIDIA DGX H100, NVIDIA DGX A100 640GB, MacBook Pro 16" M4 Max (48 GB).
Runs great
— Plenty of headroom
Where to Download Llama 3 3 Nemotron Super 49B V1
Community quantizations of this model — GGUF for llama.cpp, Ollama, and LM Studio, plus AWQ/MLX variants where available.
Benchmarks
Benchmark details →Related Models
Frequently Asked Questions
- How much VRAM does Llama 3 3 Nemotron Super 49B V1 need?
Llama 3 3 Nemotron Super 49B V1 requires 32.9 GB of VRAM at Q4_K_M, or 109.7 GB at BF16.
VRAM = Weights + KV Cache + Overhead
Weights = 49.9B × 4.8 bits ÷ 8 = 29.9 GB
KV Cache + Overhead ≈ 3 GB (at 2K context + ~0.3 GB framework)
VRAM usage by quantization
Q4_K_M32.9 GB- Can NVIDIA GeForce RTX 4090 run Llama 3 3 Nemotron Super 49B V1?
Yes, at Q3_K_S (24 GB) or lower. Higher quantizations like IQ3_M (24.7 GB) exceed the NVIDIA GeForce RTX 4090's 24 GB.
- What's the best quantization for Llama 3 3 Nemotron Super 49B V1?
For Llama 3 3 Nemotron Super 49B V1, Q4_K_M (32.9 GB) offers the best balance of quality and VRAM usage. Q4_K_L (33.6 GB) provides better quality if you have the VRAM. The smallest option is IQ2_XXS at 15.1 GB.
VRAM requirement by quantization
IQ2_XXS15.1 GBIQ3_S23.3 GBQ3_K_L28.1 GBQ4_K_M ★32.9 GBQ5_034.3 GBBF16109.7 GB★ Recommended — best balance of quality and VRAM usage.
- Can I run Llama 3 3 Nemotron Super 49B V1 on a Mac?
Llama 3 3 Nemotron Super 49B V1 requires at least 15.1 GB at IQ2_XXS, 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 locally?
Yes — Llama 3 3 Nemotron Super 49B V1 can run locally on consumer hardware. At Q4_K_M quantization it needs 32.9 GB of VRAM. Popular tools include Ollama, LM Studio, and llama.cpp.
- How fast is Llama 3 3 Nemotron Super 49B V1?
At Q4_K_M, Llama 3 3 Nemotron Super 49B V1 can reach ~146 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 ÷ 32.9 × 0.65 = ~158 tok/s
Estimated speed at Q4_K_M (32.9 GB)
~158 tok/s~158 tok/s~146 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?
At Q4_K_M, the download is about 29.92 GB. The full-precision BF16 version is 99.73 GB. The smallest option (IQ2_XXS) is 13.71 GB.
- Which GPUs can run Llama 3 3 Nemotron Super 49B V1?
No single consumer GPU has enough VRAM to run Llama 3 3 Nemotron Super 49B V1 at Q4_K_M (32.9 GB). Multi-GPU or professional hardware is required.
- Which devices can run Llama 3 3 Nemotron Super 49B V1?
29 devices with unified memory can run Llama 3 3 Nemotron Super 49B V1 at Q4_K_M (32.9 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.