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Best GPUs for Llama Models (3.1, 3.2, 3.3)

Our catalog tracks 6 Llama models (1.2B–405.9 parameters). For each, the table shows the cheapest retail GPU that fully fits it at Q4 / 8K context and the fastest retail GPU, with decode tok/s. Fit means weights + KV cache + 1 GB runtime overhead within 95% of VRAM — not weights alone. 1 of them exceed every retail GPU we track and are marked accordingly. Methodology.

#ModelParamsQ4/8K needs (GB)Best value GPU (fits)Fastest retail GPUBuy
1Llama-3.2-1B-Instruct1.2B1.9Arc B570 10GB ≈201.5 tok/s est.RTX 5090 32GB ≈950.3 tok/s est.Search Amazon (affiliate)
2Llama-3.2-3B-Instruct3.2B3.4Arc B570 10GB ≈75.6 tok/s est.RTX 5090 32GB ≈356.4 tok/s est.Search Amazon (affiliate)
3Llama-3.1-8B-Instruct8.0B7.0Arc B570 10GB ≈30.2 tok/s est.RTX 5090 32GB ≈214.3 tok/s measuredSearch Amazon (affiliate)
4Llama-3.1-70B-Instruct70.6B53.83Mac mini M4 Pro 64GB ≈5.0 tok/s measuredMac Studio M3 Ultra 96GB ≈14.1 tok/s measuredSearch Amazon (affiliate)
5Llama-3.3-70B-Instruct70.6B53.83Mac mini M4 Pro 64GB ≈2.5 tok/s est.MacBook Pro M4 Max 128GB ≈11.0 tok/s measuredSearch Amazon (affiliate)
6Llama-3.1-405B-Instruct405.9B305.25No retail GPU fits

est. = bandwidth-based estimate; measured = curated real benchmark that overrides the estimate. GPU names link to the full fit check (4K/8K/32K fit table + VRAM breakdown). MSRP is the launch list price, not live retail — Amazon prices change; click a Buy link for the current price. Models marked 'No retail GPU fits' need more VRAM than any retail card in our catalog (up to 192 GB) — see the model page for datacenter-class options.

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Arc B570 10GB vs RTX 5090 32GB · Arc B570 10GB vs Mac mini M4 Pro 64GB · Arc B570 10GB vs Mac Studio M3 Ultra 96GB · Mac mini M4 Pro 64GB vs RTX 5090 32GB · Mac Studio M3 Ultra 96GB vs RTX 5090 32GB · Mac Studio M3 Ultra 96GB vs Mac mini M4 Pro 64GB

More lists: 7B-class models · 13B-class models · 30B-class models · 70B+ models · Under $500 · Under $1,000 · Under $2,000 · 8 GB VRAM · 12 GB VRAM · 16 GB VRAM · 24 GB VRAM · For Qwen3 · For DeepSeek · For Gemma · For GLM · For coding · For reasoning · MoE picks