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: 0.24.

Qwen3 5 text Region:us Safetensors Sharded Tensorflow

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

Qwen3.5 27B Abliterated Benchmarks

LLME Score: 0.23677

^nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").

What is the LLM Explorer Rank (Score)

Qwen3.5 27B Abliterated (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

Best Alternatives to Qwen3.5 27B Abliterated

Best Alternatives	Context / RAM	Downloads	Likes
Qwen3.6 27B OBLITERATED	256K / 53.6 GB	15137	184
...2 Abliterated OptiQ 3.7bpw Mlx	256K / 13.4 GB	6727	14
Ornstein 3.6 27B RYS	256K / 56.8 GB	397	1
Qwen3.6 Solidity 27B	256K / 53.8 GB	73	6
Carnice 27B	256K / 53.7 GB	19	36
...wopus3.5 27B V3 FP8 Vllm Ready	256K / 29.4 GB	50	17
Qwopus3.5 27B V3 FP8	256K / 29.4 GB	51	6
Qwen3.6 27B Esper3.1	256K / 55.6 GB	4	9
...en3.6 27B OBLITERATED MLX 4bit	256K / 15.1 GB	646	3

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

Rank the Qwen3.5 27B Abliterated Capabilities

🆘 Have you tried this model? Rate its performance. This feedback would greatly assist ML community in identifying the most suitable model for their needs. Your contribution really does make a difference! 🌟

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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Qwen3.5 27B Abliterated by sci4ai

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Qwen3.5 27B Abliterated Benchmarks

Qwen3.5 27B Abliterated Parameters and Internals

Best Alternatives to Qwen3.5 27B Abliterated

Rank the Qwen3.5 27B Abliterated Capabilities

What open-source LLMs or SLMs are you in search of? 55446 in total.