Gemma 4 12B — VRAM Requirements
Autor: Jakub Rusinowski · Ostatnia aktualizacja: 21 lipca 2026
How much GPU VRAM you need to run Gemma 4 (Legacy Listing — Unverified) Gemma 4 12B by Google DeepMind locally, a 12B-parameter model. Figures are quantized weights + KV cache + framework overhead from a memory-bandwidth roofline model.
Gemma 4 12B needs about 8 GB VRAM at Q4_K_M.
VRAM by Quantization
| Quant | Bits/weight | Weights | Total VRAM |
|---|---|---|---|
| Q2_K | 2.63 | 3.9 GB | 4.7 GB |
| Q3_K_M | 3.41 | 5.1 GB | 5.9 GB |
| Q4_K_M | 4.83 | 7.2 GB | 8.0 GB |
| Q5_K_M | 5.67 | 8.5 GB | 9.3 GB |
| Q6_K | 6.56 | 9.8 GB | 10.6 GB |
| Q8_0 | 8.50 | 12.8 GB | 13.6 GB |
| F16 | 16.00 | 24.0 GB | 24.8 GB |
Switch quantization in the interactive calculator, or see the full Gemma 4 (Legacy Listing — Unverified) model page.
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Model creators: paste this into your Hugging Face model card README to link readers straight to this VRAM breakdown.
[](https://llmconfigurator.com/en/vram-calculator/gemma-4-legacy-12b)Estimates only — actual VRAM varies with context length, batch size, runtime and KV-cache settings.