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TextImageAudioVideo

Gemma 4 E4B VRAM Requirements

Developed by Google

Find out exactly how much VRAM you need to run Gemma 4 E4B locally. Calculate the memory footprint of different GGUF quantization variants (like Q4_K_M or Q8_0), estimate your context length KV cache VRAM footprint, and determine if your hardware supports a full GPU VRAM offload or if you will need to rely on slow partial CPU offloading to avoid a CUDA Out of Memory (OOM) error.

Hugging Face Repository

Hardware Configuration

Adjust settings to check compatibility with your system in real time.

GB VRAM

Available: 14.50 GB

GB RAM

Available: 29.00 GB

8,192 tokens
CPU Offloading
Compatibility Verdict
Fits in GPU VRAM

This model's configuration fits fully in your VRAM. You will experience peak speed and performance.

Requires 5.70 GB total memory (weights: 5.13 GB, context overhead: 0.14 GB, activation overhead: 0.42 GB).

Memory Margin+8.80 GB

Gemma 4 E4B Quantization Formats & VRAM Compatibility

Select a format to set it as active and calculate your system fit dynamically.

QuantWeightsKV CacheOverheadTotal VRAMStatusLinks
Base (Unquantized)14.89 GB0.14 GB1.20 GB
16.24 GB
CPU Offload
HF weights
UD-Q4_K_XL5.13 GB0.14 GB0.42 GB
5.70 GB
Fits in VRAM
GGUF
UD-Q8_K_XL8.71 GB0.14 GB0.71 GB
9.56 GB
Fits in VRAM
GGUF

Gemma 4 E4B KV Cache Memory Breakdown

How to Setup and Run Gemma 4 E4B Locally

1

Method A: Ollama (Recommended)

Ollama is the easiest way to run models in the background. First, download it from ollama.com, then execute this terminal command:

ollama run <model-name>
2

Method B: LM Studio (GUI)

If you prefer a full graphical interface with chat UI and local server hosting:

  • Download and install LM Studio.
  • Search for Gemma 4 E4B in the home page search tab.
  • Select a quantization level (like Q4_K_M) that fits your VRAM, click download, and load it to chat.

Model Specs

  • DeveloperGoogle
  • Parameter Count4.5B
  • Base File Size14.9 GB
  • AvailabilityLocal-Only
  • Input Modalities
    TextImageAudioVideo

Standard Benchmark Scores

Coding (LiveCodeBench)52%
Reasoning (GPQA Diamond)58.6%

Commercial API Pricing

This model is self-hosted only or official API pricing is not available.

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