What are the hardware requirements for Gemma 3 27B It Qat Abliterated?

Gemma 3 27B It Qat Abliterated requires approximately 108.9 GB of VRAM and supports a context window of 128K tokens. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Gemma 3 27B It Qat Abliterated and how large is it?

Gemma 3 27B It Qat Abliterated is developed by mlabonne, a model with 27b 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 3 27B It Qat Abliterated?

Gemma 3 27B It Qat Abliterated is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Gemma 3 27B It Qat Abliterated by mlabonne — VRAM 108.9GB, 128K context

Name: Gemma 3 27B It Qat Abliterated
Author: mlabonne

Gemma 3 27B It Qat Abliterated is an open-source language model by mlabonne. Features: 27b LLM, VRAM: 108.9GB, Context: 128K, License: gemma, Quantized.

Base model:finetune:google/gem... Base model:google/gemma-3-27b-... Conversational Endpoints compatible Gemma3 text Image-text-to-text Q4 Q4 0 Quantized Region:us Safetensors Sharded Tensorflow

Model Card on HF 🤗: https://huggingface.co/mlabonne/gemma-3-27b-it-qat-abliterated

Gemma 3 27B It Qat Abliterated Parameters and Internals

LLM Name	Gemma 3 27B It Qat Abliterated
Repository 🤗	https://huggingface.co/mlabonne/gemma-3-27b-it-qat-abliterated
Base Model(s)	google/gemma-3-27b-it-qat-q4_0-unquantized google/gemma-3-27b-it-qat-q4_0-unquantized
Model Size	27b
Required VRAM	108.9 GB
Updated	2026-08-09
Maintainer	mlabonne
Model Type	gemma3_text
Model Files	5.6 GB: 1-of-22 5.0 GB: 2-of-22 5.0 GB: 3-of-22 5.0 GB: 4-of-22 5.0 GB: 5-of-22 5.0 GB: 6-of-22 5.0 GB: 7-of-22 5.0 GB: 8-of-22 5.0 GB: 9-of-22 5.0 GB: 10-of-22 5.0 GB: 11-of-22 5.0 GB: 12-of-22 5.0 GB: 13-of-22 5.0 GB: 14-of-22 5.0 GB: 15-of-22 5.0 GB: 16-of-22 5.0 GB: 17-of-22 5.0 GB: 18-of-22 5.0 GB: 19-of-22 5.0 GB: 20-of-22 5.0 GB: 21-of-22 3.3 GB: 22-of-22
Quantization Type	q4\|q4_0
Model Architecture	Gemma3ForCausalLM
License	gemma
Context Length	131072
Model Max Length	131072
Transformers Version	4.51.3
Tokenizer Class	GemmaTokenizer
Padding Token	<pad>
Vocabulary Size	262208
Torch Data Type	float32

Rank the Gemma 3 27B It Qat 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

Best Alternatives to Gemma 3 27B It Qat Abliterated

Best Alternatives	Context / RAM	Downloads	Likes
Medgemma 27B Text It Bnb 4bit	128K / 16.1 GB	1126	3
...a 27B Text It Unsloth Bnb 4bit	128K / 16.6 GB	1050	7
Medgemma 27B Text It 4bit	128K / 16 GB	234	3
Medgemma 27B Text It 8bit	128K / 30.3 GB	129	2
Medgemma 27B Text It GPTQ 4bit	128K / 16.2 GB	648	3
Fanar 2 27B Instruct	128K / 54.4 GB	10917	11
YanoljaNEXT Rosetta 27B 2511	128K / 57.2 GB	33	35
Medgemma 27B Text Heretic Med	128K / 54.4 GB	50	8
Medgemma 27B Text It	128K / 54.4 GB	1217	8
Gemma 3 27B It Abliterated V2	128K / 108.9 GB	245	20

Note: green Score (e.g. "73.2") means that the model is better than mlabonne/gemma-3-27b-it-qat-abliterated.