prithivMLmods/gemma-4-E4B-it-GGUF overview
gemma 4 E4B it GGUF Gemma 4 E4B it from Google is a 4.5B effective parameter 8B total with Per Layer Embeddings multimodal dense model in the Gemma 4 family, o…
Runs locally from ~533.9 MB disk (4 GB VRAM class GPUs with llama.cpp / guIDE).
Repository Files & Downloads
| File | Type | Quantization | Size | Link |
|---|---|---|---|---|
| gemma-4-E4B-it.BF16.gguf | GGUF | GGUF | 14.02 GB | Download |
| gemma-4-E4B-it.F16.gguf | GGUF | GGUF | 14.02 GB | Download |
| gemma-4-E4B-it.Q2_K.gguf | GGUF | GGUF | 4.10 GB | Download |
| gemma-4-E4B-it.Q3_K_L.gguf | GGUF | GGUF | 4.68 GB | Download |
| gemma-4-E4B-it.Q3_K_M.gguf | GGUF | GGUF | 4.52 GB | Download |
| gemma-4-E4B-it.Q3_K_S.gguf | GGUF | GGUF | 4.33 GB | Download |
| gemma-4-E4B-it.Q4_0.gguf | GGUF | GGUF | 4.83 GB | Download |
| gemma-4-E4B-it.Q4_K_M.gguf | GGUF | GGUF | 4.97 GB | Download |
| gemma-4-E4B-it.Q4_K_S.gguf | GGUF | GGUF | 4.85 GB | Download |
| gemma-4-E4B-it.Q5_0.gguf | GGUF | GGUF | 5.30 GB | Download |
| gemma-4-E4B-it.Q5_K_M.gguf | GGUF | GGUF | 5.37 GB | Download |
| gemma-4-E4B-it.Q5_K_S.gguf | GGUF | GGUF | 5.30 GB | Download |
| gemma-4-E4B-it.Q6_K.gguf | GGUF | GGUF | 5.79 GB | Download |
| gemma-4-E4B-it.Q8_0.gguf | GGUF | GGUF | 7.46 GB | Download |
| gemma-4-E4B-it.mmproj-bf16.gguf | GGUF | BF16 | 945.6 MB | Download |
| gemma-4-E4B-it.mmproj-f16.gguf | GGUF | F16 | 945.6 MB | Download |
| gemma-4-E4B-it.mmproj-q8_0.gguf | GGUF | Q8_0 | 533.9 MB | Download |
Model Details
| Model ID | prithivMLmods/gemma-4-E4B-it-GGUF |
|---|---|
| Author | prithivMLmods |
| Pipeline | image-text-to-text |
| License | apache-2.0 |
| Base model | google/gemma-4-E4B-it |
| Last modified | 2026-06-07T04:55:08.000Z |
Model README
---
base_model:
- google/gemma-4-E4B-it
license: apache-2.0
language:
- en
pipeline_tag: image-text-to-text
library_name: transformers
tags:
- text-generation-inference
- llama-cpp
- moe
- e4b
---
gemma-4-E4B-it-GGUF
> Gemma-4-E4B-it from Google is a 4.5B effective parameter (8B total with Per-Layer Embeddings) multimodal dense model in the Gemma 4 family, optimized for edge deployment on laptops, high-end smartphones, and consumer GPUs with native support for text, images (variable aspect ratio/resolution), audio processing, and configurable thinking modes for step-by-step reasoning. Featuring 42 layers, 512-token sliding window, 128K context length, and 262K vocabulary, it delivers frontier-level performance in agentic workflows, multilingual OCR/handwriting recognition, document/PDF parsing, UI/screen analysis, chart interpretation, object detection with pointing, coding assistance, and low-latency speech-to-text understanding—rivaling models 10-20x larger while maintaining Google's production-grade safety alignments. The instruction-tuned variant excels at on-device autonomous agents via Android AICore/Qualcomm optimizations, with open weights enabling local-first inference (MediaTek/ARM CPUs, NVIDIA RTX) for privacy-focused applications like mobile IDEs, real-time document processing, and structured data extraction in resource-constrained environments.
Model Files
File Name | Quant Type | File Size | File Link |
|-----------|------------|-----------|-----------|
| gemma-4-E4B-it.BF16.gguf | BF16 | 15.1 GB | Download |
| gemma-4-E4B-it.F16.gguf | F16 | 15.1 GB | Download |
| gemma-4-E4B-it.Q2_K.gguf | Q2_K | 4.4 GB | Download |
| gemma-4-E4B-it.Q3_K_L.gguf | Q3_K_L | 5.02 GB | Download |
| gemma-4-E4B-it.Q3_K_M.gguf | Q3_K_M | 4.85 GB | Download |
| gemma-4-E4B-it.Q3_K_S.gguf | Q3_K_S | 4.65 GB | Download |
| gemma-4-E4B-it.Q4_0.gguf | Q4_0 | 5.19 GB | Download |
| gemma-4-E4B-it.Q4_K_M.gguf | Q4_K_M | 5.34 GB | Download |
| gemma-4-E4B-it.Q4_K_S.gguf | Q4_K_S | 5.2 GB | Download |
| gemma-4-E4B-it.Q5_0.gguf | Q5_0 | 5.69 GB | Download |
| gemma-4-E4B-it.Q5_K_M.gguf | Q5_K_M | 5.76 GB | Download |
| gemma-4-E4B-it.Q5_K_S.gguf | Q5_K_S | 5.69 GB | Download |
| gemma-4-E4B-it.Q6_K.gguf | Q6_K | 6.22 GB | Download |
| gemma-4-E4B-it.Q8_0.gguf | Q8_0 | 8.01 GB | Download |
| gemma-4-E4B-it.mmproj-bf16.gguf | mmproj-bf16 | 992 MB | Download |
| gemma-4-E4B-it.mmproj-f16.gguf | mmproj-f16 | 992 MB | Download |
| gemma-4-E4B-it.mmproj-q8_0.gguf | mmproj-q8_0 | 560 MB | Download |
llama.cpp
LLM inference in C/C++ — https://github.com/ggml-org/llama.cpp
Run prithivMLmods/gemma-4-E4B-it-GGUF with guIDE
Download guIDE — the AI-native code editor with local LLM inference and 69 built-in tools.
Source: Hugging Face · Compare models