What are the hardware requirements for Qwen3.5 27B Abliterated?

Qwen3.5 27B Abliterated requires approximately 53.8 GB of VRAM and supports a context window of 256K tokens. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Qwen3.5 27B Abliterated and how large is it?

Qwen3.5 27B Abliterated is developed by sci4ai, 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 Qwen3.5 27B Abliterated?

Qwen3.5 27B Abliterated is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Qwen3.5 27B Abliterated by sci4ai — VRAM 53.8GB, 256K context

Name: Qwen3.5 27B Abliterated
Author: sci4ai

Qwen3.5 27B Abliterated is an open-source language model by sci4ai. Features: 27b LLM, VRAM: 53.8GB, Context: 256K, LLM Explorer Score: 0.22.

Qwen3 5 text Region:us Safetensors Sharded Tensorflow

Model Card on HF 🤗: https://huggingface.co/sci4ai/Qwen3.5-27B-Abliterated

Qwen3.5 27B Abliterated Parameters and Internals

LLM Name	Qwen3.5 27B Abliterated
Repository 🤗	https://huggingface.co/sci4ai/Qwen3.5-27B-Abliterated
Model Size	27b
Required VRAM	53.8 GB
Updated	2026-04-24
Maintainer	sci4ai
Model Type	qwen3_5_text
Model Files	49.8 GB: 1-of-2 4.0 GB: 2-of-2
Model Architecture	Qwen3_5ForCausalLM
Context Length	262144
Model Max Length	262144
Transformers Version	5.5.4
Tokenizer Class	TokenizersBackend
Padding Token	<\|endoftext\|>
Vocabulary Size	248320
Errors	replace

Rank the Qwen3.5 27B Abliterated capabilities

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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 Qwen3.5 27B Abliterated

Best Alternatives	Context / RAM	Downloads	Likes
Hemmingway 1	256K / 53.8 GB	12371	880
Hemmingway 1	256K / 53.8 GB	9089	888
JEV 27B	256K / 53.9 GB	178643	79
OrcaSAQ 2 27B	256K / 12.3 GB	1330	169
Qwen3.6 27B OBLITERATED	256K / 53.6 GB	15137	184
Darwin 27B RSI	256K / 53.8 GB	459	14
RAG Gate 27B	256K / 53.8 GB	243	0
Mnma Qwen3.8 27b Nvfp4	256K / 18.8 GB	527	11
...2 Abliterated OptiQ 3.7bpw Mlx	256K / 13.4 GB	6727	14
...2 Abliterated OptiQ 3.7bpw Mlx	256K / 13.4 GB	5919	14

Note: green Score (e.g. "73.2") means that the model is better than sci4ai/Qwen3.5-27B-Abliterated.