your 8GB graphics card can run real local AI — you're probably picking the wrong model

Phi-4 Mini, Gemma 3, and Llama 3.2 all claim to fit — I checked which one actually leaves room to breathe.

Aliteq
Lena Fischer · AI & Local Compute Editor

Key point

Phi-4 Mini is 3.8B parameters with a genuine 128K context window and needs only about 2.2-2.4GB of VRAM at Q4 — the lightest of the three.

Key point

Gemma 3 12B needs roughly 6.6-6.7GB at Q4 and still fits an 8GB card, despite being 3x the parameter count of Phi-4 Mini.

Key point

Gemma 3 4B fits at full Q8 precision on an 8GB card with room to spare — no quantization compromise needed.

Key point

Llama 3.2 3B needs only 2-3GB at Q4_K_M and is the fastest of the three, but it's also the weakest reasoner.

Key point

All three claim up to 128K context, but VRAM for the KV cache is separate from model weights — the bigger the model, the less context headroom you actually get.

Best local AI model for an 8GB GPU

Gemma 3 12B for the best reasoning quality that still fits comfortably. Phi-4 Mini when you genuinely need long context on tight VRAM. Llama 3.2 3B when speed matters more than depth. There isn't…

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your 8GB graphics card can run real local AI — you're probably picking the wrong model

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