Llama 3.2 3B Wildguard Ko 2410 — Hardware Requirements & GPU Compatibility
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Llama 3.2 3B Wildguard Ko 2410 is a 3.2B-parameter open language model from iknow-lab in the Llama 3 family. It supports a context window of up to 131,072 tokens. At Q4_K_M it needs about 2.46 GB of VRAM — see which GPUs and Macs can run it below.
325 downloads
5 likesSpecifications
- Publisher
- iknow-lab
- Family
- Llama 3
- Parameters
- 3.2B
- Architecture
- LlamaForCausalLM
- Context Length
- 131,072 tokens
- Vocabulary Size
- 128,256
- Release Date
- 2024-10-25
- License
- llama3.2
Get Started
HuggingFace
How Much VRAM Does Llama 3.2 3B Wildguard Ko 2410 Need?
Select a quantization to see compatible GPUs below.
| Quantization | Bits | VRAM | + Context | File Size | Quality |
|---|---|---|---|---|---|
| Q2_K | 3.40 | 1.9 GB | 16.7 GB | 1.37 GB | 2-bit quantization with K-quant improvements |
| Q3_K_S | 3.50 | 1.9 GB | 16.7 GB | 1.41 GB | 3-bit small quantization |
| Q3_K_M | 3.90 | 2.1 GB | 16.9 GB | 1.57 GB | 3-bit medium quantization |
| Q4_K_M | 4.80 | 2.5 GB | 17.3 GB | 1.93 GB | 4-bit medium quantization — most popular sweet spot |
| Q5_K_M | 5.70 | 2.8 GB | 17.6 GB | 2.29 GB | 5-bit medium quantization — good quality/size tradeoff |
| Q6_K | 6.60 | 3.2 GB | 18.0 GB | 2.65 GB | 6-bit quantization, very good quality |
| Q8_0 | 8.00 | 3.8 GB | 18.6 GB | 3.21 GB | 8-bit quantization, near-lossless |
Which GPUs Can Run Llama 3.2 3B Wildguard Ko 2410?
Q4_K_M · 2.5 GBLlama 3.2 3B Wildguard Ko 2410 (Q4_K_M) requires 2.5 GB of VRAM to load the model weights. For comfortable inference with headroom for KV cache and system overhead, 4+ GB is recommended. Using the full 131K context window can add up to 14.8 GB, bringing total usage to 17.3 GB. 50 GPUs can run it, including NVIDIA GeForce RTX 5090, NVIDIA GeForce RTX 3090 Ti.
Runs great
— Plenty of headroomWhich Devices Can Run Llama 3.2 3B Wildguard Ko 2410?
Q4_K_M · 2.5 GB59 devices with unified memory can run Llama 3.2 3B Wildguard Ko 2410, including NVIDIA DGX H100, NVIDIA DGX A100 640GB.
Runs great
— Plenty of headroomWhere to Download Llama 3.2 3B Wildguard Ko 2410
Community quantizations of this model — GGUF for llama.cpp, Ollama, and LM Studio, plus AWQ/MLX variants where available.
Related Models
Frequently Asked Questions
- How much VRAM does Llama 3.2 3B Wildguard Ko 2410 need?
Llama 3.2 3B Wildguard Ko 2410 requires 2.5 GB of VRAM at Q4_K_M, or 7.0 GB at FP16. Full 131K context adds up to 14.8 GB (17.3 GB total).
VRAM = Weights + KV Cache + Overhead
Weights = 3.2B × 4.8 bits ÷ 8 = 1.9 GB
KV Cache + Overhead ≈ 0.6 GB (at 2K context + ~0.3 GB framework)
KV Cache + Overhead ≈ 15.4 GB (at full 131K context)
VRAM usage by quantization
Q4_K_M2.5 GBQ4_K_M + full context17.3 GB- What's the best quantization for Llama 3.2 3B Wildguard Ko 2410?
For Llama 3.2 3B Wildguard Ko 2410, Q4_K_M (2.5 GB) offers the best balance of quality and VRAM usage. Q5_K_S (2.7 GB) provides better quality if you have the VRAM. The smallest option is Q2_K at 1.9 GB.
VRAM requirement by quantization
Q2_K1.9 GBQ3_K_L2.2 GBQ4_K_M ★2.5 GBQ5_K_S2.7 GBQ5_K_M2.8 GBFP167.0 GB★ Recommended — best balance of quality and VRAM usage.
- Can I run Llama 3.2 3B Wildguard Ko 2410 on a Mac?
Llama 3.2 3B Wildguard Ko 2410 requires at least 1.9 GB at Q2_K, 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 3.2 3B Wildguard Ko 2410 locally?
Yes — Llama 3.2 3B Wildguard Ko 2410 can run locally on consumer hardware. At Q4_K_M quantization it needs 2.5 GB of VRAM. Popular tools include Ollama, LM Studio, and llama.cpp.
- How fast is Llama 3.2 3B Wildguard Ko 2410?
At Q4_K_M, Llama 3.2 3B Wildguard Ko 2410 can reach ~1789 tok/s on AMD Instinct MI350X. On NVIDIA GeForce RTX 4090: ~266 tok/s. 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 ÷ 2.5 × 0.65 = ~2114 tok/s
Estimated speed at Q4_K_M (2.5 GB)
~2114 tok/s~266 tok/s~2114 tok/s~1789 tok/sReal-world results typically within ±20%. Speed depends on batch size, quantization kernel, and software stack.
- What's the download size of Llama 3.2 3B Wildguard Ko 2410?
At Q4_K_M, the download is about 1.93 GB. The full-precision FP16 version is 6.43 GB. The smallest option (Q2_K) is 1.37 GB.
- Which GPUs can run Llama 3.2 3B Wildguard Ko 2410?
50 consumer GPUs can run Llama 3.2 3B Wildguard Ko 2410 at Q4_K_M (2.5 GB). Top options include AMD Radeon RX 6700 XT, AMD Radeon RX 6800, AMD Radeon RX 6800 XT. 50 GPUs have plenty of headroom for comfortable inference.
- Which devices can run Llama 3.2 3B Wildguard Ko 2410?
59 devices with unified memory can run Llama 3.2 3B Wildguard Ko 2410 at Q4_K_M (2.5 GB), including AMD Ryzen AI 9 HX 370 (Strix Point) Laptop, ASUS Ascent GX10, Apple iPhone 17 Pro, Asus ROG Flow Z13 (2025, 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.