Google Gemma 4 E4B Multimodal VRAM Requirements Guide
Efficient 4.4B edge multimodal model with 5:1 hybrid sliding-window attention. High vision-audio reasoning speed fitting easily on 6GB–8GB GPUs.
>98.2% retention. 2.6 GB weights, leaving +7.3 GB headroom on Intel Arc B580 12GB.
Near-lossless 8-bit precision requiring 6.9 GB VRAM for benchmark evaluations.
Uncompressed FP16 weights taking 11.1 GB. Demands multi-GPU or datacenter accelerators.
Architectural Memory Breakdown & Attention Scaling
Gemma 4 E4B is a 4.2B parameter edge multimodal model incorporating Google's 5:1 Sliding Window Attention ratio across 28 layers (23 local sliding layers with 1,024-token window, 5 global layers with 2 KV heads and `headDim = 256`). At 8k context, KV-cache requires only 0.45 GiB, while 4-bit Q4_K_M weights occupy 2.8 GB, bringing total memory to 3.8 GB. It delivers high-speed multimodal reasoning on 6GB–8GB GPUs.
In Ollama, pass `OLLAMA_FLASH_ATTENTION=1`. Thanks to 5:1 SWA, context scaling to 16k tokens adds less than 0.6 GB of KV-cache, allowing extended document analysis inside 4.5 GB VRAM on budget graphics cards.
Intel Arc B580 12GB provides 12.0 GB physical VRAM (+7.3 GB operational margin at 8k context).
Run Google Gemma 4 E4B Multimodal Locally
ollama run gemma-4-e4b:q4_K_Mvllm serve Google DeepMind/gemma-4-e4b --max-model-len 8192 --gpu-memory-utilization 0.95Frequently Asked Questions
How does Gemma 4 E4B compare against LLaMA 3.2 3B?
Gemma 4 E4B includes native vision understanding and 5:1 SWA for bounded KV-cache growth, whereas LLaMA 3.2 3B is a text-only full-attention model.
Can Gemma 4 E4B run on an 8GB gaming laptop?
Easily! Consuming under 4.0 GB VRAM at Q4_K_M, it runs at over 85 tok/s on 6GB and 8GB laptop graphics cards while leaving ample memory for gaming and desktop apps.
Test Custom Hardware & Context Windows
Simulate Google Gemma 4 E4B Multimodal across all 31 GPUs, adjust context up to 131,072 tokens, or calculate RunPod break-even costs.
Open Google Gemma 4 E4B Multimodal in GPU Garden Matchmaker →