Meta Llama Guard 2 8B — Hardware Requirements & GPU Compatibility
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Meta Llama Guard 2 8B is a 8.0B-parameter open language model from Meta in the Llama family. At BF16 it needs about 17.67 GB of VRAM — see which GPUs and Macs can run it below.
8.3K downloads
307 likesSpecifications
- Publisher
- Meta
- Family
- Llama
- Parameters
- 8.0B
- Release Date
- 2024-05-13
- License
- Llama 3 Community
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HuggingFace
How Much VRAM Does Meta Llama Guard 2 8B Need?
Select a quantization to see compatible GPUs below.
| Quantization | Bits | VRAM | + Context | File Size | Quality |
|---|---|---|---|---|---|
| BF16 | 16.00 | 17.7 GB | — | 16.06 GB | Brain floating point 16 — preferred for training |
Which GPUs Can Run Meta Llama Guard 2 8B?
BF16 · 17.7 GBMeta Llama Guard 2 8B (BF16) requires 17.7 GB of VRAM to load the model weights. For comfortable inference with headroom for KV cache and system overhead, 23+ GB is recommended. 6 GPUs can run it, including NVIDIA GeForce RTX 5090, NVIDIA GeForce RTX 3090 Ti.
Runs great
— Plenty of headroom
Which Devices Can Run Meta Llama Guard 2 8B?
BF16 · 17.7 GB21 devices with unified memory can run Meta Llama Guard 2 8B, including NVIDIA DGX H100, NVIDIA DGX A100 640GB, Mac Mini M4 Pro (24 GB).
Runs great
— Plenty of headroomRelated Models
Frequently Asked Questions
- How much VRAM does Meta Llama Guard 2 8B need?
Meta Llama Guard 2 8B requires 17.7 GB of VRAM at BF16.
VRAM = Weights + KV Cache + Overhead
Weights = 8.0B × 16 bits ÷ 8 = 16.1 GB
KV Cache + Overhead ≈ 1.6 GB (at 2K context + ~0.3 GB framework)
VRAM usage by quantization
BF1617.7 GB- Can I run Meta Llama Guard 2 8B on a Mac?
Meta Llama Guard 2 8B requires at least 17.7 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 Meta Llama Guard 2 8B locally?
Yes — Meta Llama Guard 2 8B can run locally on consumer hardware. At BF16 quantization it needs 17.7 GB of VRAM. Popular tools include Ollama, LM Studio, and llama.cpp.
- How fast is Meta Llama Guard 2 8B?
At BF16, Meta Llama Guard 2 8B can reach ~165 tok/s on AMD Instinct MI300X. On NVIDIA GeForce RTX 4090: ~37 tok/s. 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 ÷ 17.7 × 0.55 = ~165 tok/s
Estimated speed at BF16 (17.7 GB)
~165 tok/s~37 tok/s~123 tok/s~102 tok/sReal-world results typically within ±20%. Speed depends on batch size, quantization kernel, and software stack.
- What's the download size of Meta Llama Guard 2 8B?
At BF16, the download is about 16.06 GB.
- Which GPUs can run Meta Llama Guard 2 8B?
6 consumer GPUs can run Meta Llama Guard 2 8B at BF16 (17.7 GB). Top options include NVIDIA GeForce RTX 5090, AMD Radeon RX 7900 XT, AMD Radeon RX 7900 XTX. 1 GPU have plenty of headroom for comfortable inference.
- Which devices can run Meta Llama Guard 2 8B?
21 devices with unified memory can run Meta Llama Guard 2 8B at BF16 (17.7 GB), including Mac Mini M4 (32 GB), Mac Mini M4 Pro (24 GB), Mac Mini M4 Pro (48 GB), Mac Pro M2 Ultra (192 GB). Apple Silicon Macs use unified memory shared between CPU and GPU, making them well-suited for local LLM inference.