Llama 4 Scout 17B 16E Instruct — Hardware Requirements & GPU Compatibility
Vision
Llama 4 Scout 17B 16E Instruct is a 108.6B-parameter open language model from Meta in the Llama 4 family. At Q4_K_M it needs about 71.70 GB of VRAM — see which GPUs and Macs can run it below.
438.5K downloads
1.3K likesSpecifications
- Publisher
- Meta
- Family
- Llama 4
- Parameters
- 108.6B
- Release Date
- 2025-04-02
- License
- Other
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HuggingFace
How Much VRAM Does Llama 4 Scout 17B 16E Instruct Need?
Select a quantization to see compatible GPUs below.
| Quantization | Bits | VRAM | + Context | File Size | Quality |
|---|---|---|---|---|---|
| Q2_K | 3.40 | 50.8 GB | — | 46.17 GB | 2-bit quantization with K-quant improvements |
| Q3_K_S | 3.50 | 52.3 GB | — | 47.53 GB | 3-bit small quantization |
| Q3_K_M | 3.90 | 58.3 GB | — | 52.96 GB | 3-bit medium quantization |
| Q4_0 | 4.00 | 59.8 GB | — | 54.32 GB | 4-bit legacy quantization |
| Q4_K_M | 4.80 | 71.7 GB | — | 65.19 GB | 4-bit medium quantization — most popular sweet spot |
| Q5_K_M | 5.70 | 85.2 GB | — | 77.41 GB | 5-bit medium quantization — good quality/size tradeoff |
| Q6_K | 6.60 | 98.6 GB | — | 89.63 GB | 6-bit quantization, very good quality |
| Q8_0 | 8.00 | 119.5 GB | — | 108.64 GB | 8-bit quantization, near-lossless |
Which GPUs Can Run Llama 4 Scout 17B 16E Instruct?
Q4_K_M · 71.7 GBLlama 4 Scout 17B 16E Instruct (Q4_K_M) requires 71.7 GB of VRAM to load the model weights. For comfortable inference with headroom for KV cache and system overhead, 94+ GB is recommended. No single GPU has enough memory — multi-GPU or cluster setups are needed.
Which Devices Can Run Llama 4 Scout 17B 16E Instruct?
Q4_K_M · 71.7 GB19 devices with unified memory can run Llama 4 Scout 17B 16E Instruct, including NVIDIA DGX H100, NVIDIA DGX A100 640GB, Mac Studio (M3 Ultra, 96GB).
Runs great
— Plenty of headroom
Decent
— Enough memory, may be tightWhere to Download Llama 4 Scout 17B 16E Instruct
Community quantizations of this model — GGUF for llama.cpp, Ollama, and LM Studio, plus AWQ/MLX variants where available.
Benchmarks
Benchmark details →Frequently Asked Questions
- How much VRAM does Llama 4 Scout 17B 16E Instruct need?
Llama 4 Scout 17B 16E Instruct requires 71.7 GB of VRAM at Q4_K_M, or 239.0 GB at BF16.
VRAM = Weights + KV Cache + Overhead
Weights = 108.6B × 4.8 bits ÷ 8 = 65.2 GB
KV Cache + Overhead ≈ 6.5 GB (at 2K context + ~0.3 GB framework)
VRAM usage by quantization
Q4_K_M71.7 GB- Can NVIDIA GeForce RTX 5090 run Llama 4 Scout 17B 16E Instruct?
No — Llama 4 Scout 17B 16E Instruct requires at least 32.9 GB at IQ2_XXS, which exceeds the NVIDIA GeForce RTX 5090's 32 GB of VRAM.
- What's the best quantization for Llama 4 Scout 17B 16E Instruct?
For Llama 4 Scout 17B 16E Instruct, Q4_K_M (71.7 GB) offers the best balance of quality and VRAM usage. Q5_K_S (82.2 GB) provides better quality if you have the VRAM. The smallest option is IQ2_XXS at 32.9 GB.
VRAM requirement by quantization
IQ2_XXS32.9 GBQ3_K_S52.3 GBQ4_167.2 GBQ4_K_M ★71.7 GBQ5_K_S82.2 GBBF16239.0 GB★ Recommended — best balance of quality and VRAM usage.
- Can I run Llama 4 Scout 17B 16E Instruct on a Mac?
Llama 4 Scout 17B 16E Instruct requires at least 32.9 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 4 Scout 17B 16E Instruct locally?
Yes — Llama 4 Scout 17B 16E Instruct can run locally on consumer hardware. At Q4_K_M quantization it needs 71.7 GB of VRAM. Popular tools include Ollama, LM Studio, and llama.cpp.
- How fast is Llama 4 Scout 17B 16E Instruct?
At Q4_K_M, Llama 4 Scout 17B 16E Instruct can reach ~61 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 ÷ 71.7 × 0.65 = ~73 tok/s
Estimated speed at Q4_K_M (71.7 GB)
~73 tok/s~73 tok/s~61 tok/sReal-world results typically within ±20%. Speed depends on batch size, quantization kernel, and software stack.
- What's the download size of Llama 4 Scout 17B 16E Instruct?
At Q4_K_M, the download is about 65.19 GB. The full-precision BF16 version is 217.28 GB. The smallest option (IQ2_XXS) is 29.88 GB.
- Which GPUs can run Llama 4 Scout 17B 16E Instruct?
No single consumer GPU has enough VRAM to run Llama 4 Scout 17B 16E Instruct at Q4_K_M (71.7 GB). Multi-GPU or professional hardware is required.
- Which devices can run Llama 4 Scout 17B 16E Instruct?
19 devices with unified memory can run Llama 4 Scout 17B 16E Instruct at Q4_K_M (71.7 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.