What are the hardware requirements for SuperQwen3.8 27B Abliterated?

SuperQwen3.8 27B Abliterated requires approximately 55.6 GB of VRAM. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed SuperQwen3.8 27B Abliterated and how large is it?

SuperQwen3.8 27B Abliterated is developed by Jiunsong, 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 SuperQwen3.8 27B Abliterated?

SuperQwen3.8 27B Abliterated is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

SuperQwen3.8 27B Abliterated by Jiunsong — VRAM 55.6GB

Name: SuperQwen3.8 27B Abliterated
Author: Jiunsong

SuperQwen3.8 27B Abliterated is an open-source language model by Jiunsong. Features: 27b LLM, VRAM: 55.6GB, License: apache-2.0, LLM Explorer Score: 0.41.

Model Card on HF 🤗: https://huggingface.co/Jiunsong/SuperQwen3.8-27b-abliterated

SuperQwen3.8 27B Abliterated Parameters and Internals

LLM Name	SuperQwen3.8 27B Abliterated
Repository 🤗	https://huggingface.co/Jiunsong/SuperQwen3.8-27b-abliterated
Base Model(s)	Qwen/Qwen3.8-27B Qwen/Qwen3.8-27B
Model Size	27b
Required VRAM	55.6 GB
Updated	2026-08-25
Maintainer	Jiunsong
Model Type	qwen3_5
Model Files	4.0 GB: 1-of-18 3.0 GB: 2-of-18 2.5 GB: 3-of-18 4.0 GB: 4-of-18 2.1 GB: 5-of-18 4.0 GB: 6-of-18 2.1 GB: 7-of-18 4.0 GB: 8-of-18 2.1 GB: 9-of-18 4.0 GB: 10-of-18 2.1 GB: 11-of-18 4.0 GB: 12-of-18 2.1 GB: 13-of-18 4.0 GB: 14-of-18 2.1 GB: 15-of-18 4.0 GB: 16-of-18 2.1 GB: 17-of-18 3.4 GB: 18-of-18
Supported Languages	en ko
Model Architecture	Qwen3_5ForConditionalGeneration
License	apache-2.0
Model Max Length	262144
Transformers Version	5.8.0.dev0
Tokenizer Class	Qwen2Tokenizer
Padding Token	<\|endoftext\|>
Errors	replace

Rank the SuperQwen3.8 27B 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 SuperQwen3.8 27B Abliterated

Best Alternatives	Context / RAM	Downloads	Likes
Qwen3.8 27B MLX	0K / 16 GB	1411	18
Qwen3.8 27B FP8	0K / 0.4 GB	123157	416
Qwen3.8 27B	0K / 55.6 GB	2727	21
Qwen3.6 27B	0K / 55.4 GB	6728138	2197
Qwen3.8 27B	0K / 55.6 GB	2	8753
Qwen3.6 27B NVFP4	0K / 22 GB	1887525	419
ThinkingCap Qwen3.6 27B	0K / 54.7 GB	35947	614
Qwen3.6 27B FP8	0K / 0.4 GB	7740472	342
Qwen3.5 27B	0K / 55.2 GB	2536294	1028
Qwen3.8 27B Escha W2	0K / 10.1 GB	561	97

Note: green Score (e.g. "73.2") means that the model is better than Jiunsong/SuperQwen3.8-27b-abliterated.