Gemma 4 E2B — VRAM Requirements
Written by Jakub Rusinowski · Last updated July 21, 2026
How much GPU VRAM you need to run Gemma 4 Gemma 4 E2B by Google locally, a 5.1B-parameter model. Figures are quantized weights + KV cache + framework overhead from a memory-bandwidth roofline model.
Gemma 4 E2B needs about 4 GB VRAM at Q4_K_M.
VRAM by Quantization
| Quant | Bits/weight | Weights | Total VRAM |
|---|---|---|---|
| Q2_K | 2.63 | 1.7 GB | 2.5 GB |
| Q3_K_M | 3.41 | 2.2 GB | 3.0 GB |
| Q4_K_M | 4.83 | 3.1 GB | 3.9 GB |
| Q5_K_M | 5.67 | 3.6 GB | 4.4 GB |
| Q6_K | 6.56 | 4.2 GB | 5.0 GB |
| Q8_0 | 8.50 | 5.4 GB | 6.2 GB |
| F16 | 16.00 | 10.2 GB | 11.0 GB |
Switch quantization in the interactive calculator, or see the full Gemma 4 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-e2b)Estimates only — actual VRAM varies with context length, batch size, runtime and KV-cache settings.