What are the hardware requirements for Gemma 4 E2B It Abliterated?

Gemma 4 E2B It Abliterated requires approximately 10.2 GB of VRAM. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Gemma 4 E2B It Abliterated and how large is it?

Gemma 4 E2B It Abliterated is developed by anlord, a model with 5.1b parameters. The model is published as open weights on Hugging Face and indexed on LLM Explorer with full benchmark history.

Where can I download or evaluate Gemma 4 E2B It Abliterated?

Gemma 4 E2B It Abliterated is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Gemma 4 E2B It Abliterated by anlord — VRAM 10.2GB

Name: Gemma 4 E2B It Abliterated
Author: anlord

Gemma 4 E2B It Abliterated is an open-source language model by anlord. Features: 5.1b LLM, VRAM: 10.2GB, License: gemma, LLM Explorer Score: 0.28.

Abliterated Base model:finetune:google/gem... Base model:google/gemma-4-e2b-... Conversational Dataset:mlabonne/harmful behav... Dataset:mlabonne/harmless alpa... Decensored Direct-steering En Endpoints compatible Gemma4 Image-text-to-text Model-index Refusal-direction Region:us Safetensors Sharded Tensorflow Uncensored

Model Card on HF 🤗: https://huggingface.co/anlord/gemma-4-E2B-it-abliterated

Gemma 4 E2B It Abliterated Parameters and Internals

LLM Name	Gemma 4 E2B It Abliterated
Repository 🤗	https://huggingface.co/anlord/gemma-4-E2B-it-abliterated
Base Model(s)	Gemma 4 E2B It google/gemma-4-E2B-it
Model Size	5.1b
Required VRAM	10.2 GB
Updated	2026-10-13
Maintainer	anlord
Model Type	gemma4
Model Files	1.4 GB: 1-of-3 5.0 GB: 2-of-3 3.8 GB: 3-of-3
Supported Languages	en
Model Architecture	Gemma4ForConditionalGeneration
License	gemma
Transformers Version	5.19.0
Tokenizer Class	GemmaTokenizer
Padding Token	<pad>

Rank the Gemma 4 E2B It Abliterated capabilities

Have you tried this model? Rate its performance — this feedback helps the ML community find the right model for their needs.

Instruction Following and Task Automation
Factuality and Completeness of Knowledge
Censorship and Alignment
Data Analysis and Insight Generation
Text Generation
Text Summarization and Feature Extraction
Code Generation
Multi-Language Support and Translation

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Gemma 4 E2B It	0K / 10.2 GB	3222438	654
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Gemma 4 E2B It Heretic	0K / 10.2 GB	1340	0
Gemma 4 E2B It	0K / 10.2 GB	69653	13
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My Brain V2	0K / 10.3 GB	27	1

Note: green Score (e.g. "73.2") means that the model is better than anlord/gemma-4-E2B-it-abliterated.