Why Llama Guard 4 12B pressures system RAM
Llama Guard 4 12B is a dense 12B network — every weight participates each token, so quantization choice dominates. Q4_K_M lands near ~6.8GB weights, plus ~0.03GB KV at 8K and ~6GB overhead (~12.8GB → 16GB kit). The 1M-token context ceiling is the sleeper cost: long-doc or agent traces inflate KV while the 12B slab stays fixed. Prefer dual-channel DDR5 bandwidth when CPU offload or mmap is involved.
What RAM kit to buy
A 16GB dual-channel kit is enough for quantized Llama Guard 4 12B at modest context. Still prefer 2× matched SO-DIMM/UDIMM sticks; 1x RTX 4060 Ti (16GB VRAM) or RTX 4070 (12GB VRAM) covers the Budget / Entry GPU GPU profile. If you chat with long pastes, jump a tier before the KV cache forces paging.
Workload notes
Meta Llama-family models like Llama Guard 4 12B have broad llama.cpp/Ollama support — prioritize stable JEDEC/EXPO kits over unproven XMP outliers for multi-hour serves. At 12B, Llama Guard 4 12B is compact enough for laptops and mini-PCs when quantized; dual-channel memory still matters for 1% token latency. Release window noted as 2025/2026; always re-check the model card before buying hardware for a specific checkpoint.