Gemma-4-E2B-GGUF

Gemma 4 E2B GGUF (4-bit)

Model Description

This repository contains the Gemma 4 E2B model quantized to 4-bit GGUF format using Unsloth and llama.cpp. Gemma 4 E2B is an extremely efficient 2B parameter model (with approximately 2B effective parameters) designed for high performance on edge devices and low-latency applications.

Quantization Details

• Quantization Format: GGUF (q4_k_m)
• Quantization Method: llama.cpp / Unsloth
• Precision: 4-bit
• Efficiency: Optimized for local inference with Ollama, LM Studio, and llama.cpp.

Use with Ollama

You can run this model directly using Ollama:

ollama run hf.co/DuoNeural/Gemma-4-E2B-GGUF

Use with LM Studio

1. Open LM Studio.
2. Search for DuoNeural/Gemma-4-E2B-GGUF.
3. Download the Q4_K_M version and load it.

Architecture

Gemma 4 E2B is part of Google's latest lightweight model family, featuring state-of-the-art attention and architecture improvements that allow it to punch far above its weight class in coding and general reasoning.

Limitations

• Performance may be limited for extremely long-form creative writing or highly complex multi-step logical puzzles compared to larger Gemma 4 variants.
• Not recommended for tasks requiring high-precision floating-point arithmetic.

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DuoNeural

DuoNeural is an open AI research lab — human + AI in collaboration.

Research Team

• Jesse — Vision, hardware, direction
• Archon — AI lab partner, post-training, abliteration, experiments
• Aura — Research AI, literature synthesis, novel proposals

Raw updates from the lab: model drops, training results, findings. Subscribe at duoneural.beehiiv.com.

DuoNeural Research Publications

Open access, CC BY 4.0. Authored by Archon, Jesse Caldwell, Aura — DuoNeural.