Model Intelligence Sheet
FreedomAISVR/Gemma-4-E2B-it-MXFP4-GGUF overview
Gemma 4 E2B IT — MXFP4 GGUF Base Model Model: google/gemma 4 E2B it https://huggingface.co/google/gemma 4 E2B it Architecture: Gemma4ForConditionalGeneration V…
Runs locally from ~940.0 MB disk (4 GB VRAM class GPUs with llama.cpp / guIDE).
Repository Files & Downloads
Model Details
| Model ID | FreedomAISVR/Gemma-4-E2B-it-MXFP4-GGUF |
|---|---|
| Author | FreedomAISVR |
| Pipeline | — |
| License | apache-2.0 |
| Base model | google/gemma-4-E2B-it |
| Last modified | 2026-09-16T17:10:15.000Z |
Model README
---
tags:
- gguf
- conversational
- mxfp4
- vision
library_name: llama.cpp
license: apache-2.0
base_model: google/gemma-4-E2B-it
---
Gemma 4 E2B IT — MXFP4 GGUF
Base Model
- Model: google/gemma-4-E2B-it
- Architecture: Gemma4ForConditionalGeneration (Vision + Text)
- Parameters: ~3B (E2B = Efficient 2B-class)
- Context Length: 131,072 tokens (128K)
- License: Apache 2.0
- Update Date: July 20, 2026
Quantization Details
- Format: MXFP4 (OCP Microscaled FP4)
- BPW: 5.66 bits per weight
- File Size: 3.3 GB
- Non-expert tensors: F16
Vision Support
- mmproj:
mmproj-gemma-4-E2B-it-f16.gguf(985 MB, F16) - Supports image and video input
Performance (RTX 5060 Ti 16GB)
- Generation Speed: ~153 t/s at 128K context
- Context: 128K with Q8_0 KV cache fits in 16GB VRAM
Usage (llama.cpp)
llama-cli -m gemma-4-e2b-it-mxfp4.gguf -ngl 99 --flash-attn on -c 131072 --cache-type-k q8_0 --cache-type-v q8_0Why No MTP?
The Gemma 4 E2B model does not include MTP (Multi-Token Prediction) heads.
Hardware Target
- NVIDIA RTX 50 series (Blackwell) for MXFP4 acceleration
- 16GB+ VRAM recommended
Run FreedomAISVR/Gemma-4-E2B-it-MXFP4-GGUF with guIDE
Download guIDE — the AI-native code editor with local LLM inference and 69 built-in tools.
Source: Hugging Face · Compare models