What are the hardware requirements for Qwen3.8 27B Abliterated AWQ INT4?

Qwen3.8 27B Abliterated AWQ INT4 requires approximately 17.6 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 Qwen3.8 27B Abliterated AWQ INT4 and how large is it?

Qwen3.8 27B Abliterated AWQ INT4 is developed by hotdogs, 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 Qwen3.8 27B Abliterated AWQ INT4?

Qwen3.8 27B Abliterated AWQ INT4 is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Qwen3.8 27B Abliterated AWQ INT4 by hotdogs — VRAM 17.6GB, 256K context

Name: Qwen3.8 27B Abliterated AWQ INT4
Author: hotdogs

Qwen3.8 27B Abliterated AWQ INT4 is an open-source language model by hotdogs. Features: 27b LLM, VRAM: 17.6GB, Context: 256K, License: apache-2.0, Quantized, LLM Explorer Score: 0.28.

Abliterated Awq Base model:hotdogs/qwen3.8-27b... Base model:quantized:hotdogs/q... Compressed-tensors Conversational En Endpoints compatible Gptq Int4 Quantized Qwen3 5 Qwen3 5 text Region:us Safetensors Th Uncensored Vllm W4a16 Zh

Model Card on HF 🤗: https://huggingface.co/hotdogs/Qwen3.8-27B-abliterated-AWQ-INT4

Qwen3.8 27B Abliterated AWQ INT4 Parameters and Internals

LLM Name	Qwen3.8 27B Abliterated AWQ INT4
Repository 🤗	https://huggingface.co/hotdogs/Qwen3.8-27B-abliterated-AWQ-INT4
Base Model(s)	hotdogs/Qwen3.8-27B-abliterated hotdogs/Qwen3.8-27B-abliterated
Model Size	27b
Required VRAM	17.6 GB
Updated	2026-09-21
Maintainer	hotdogs
Model Type	qwen3_5_text
Model Files	17.6 GB
Supported Languages	en zh th
AWQ Quantization	Yes
Quantization Type	awq
Model Architecture	Qwen3_5ForCausalLM
License	apache-2.0
Context Length	262144
Model Max Length	262144
Transformers Version	5.15.0
Tokenizer Class	Qwen2Tokenizer
Padding Token	<\|endoftext\|>
Vocabulary Size	248320
Errors	replace

Rank the Qwen3.8 27B Abliterated AWQ INT4 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 Qwen3.8 27B Abliterated AWQ INT4

Best Alternatives	Context / RAM	Downloads	Likes
...en3.6 27B OBLITERATED MLX 4bit	256K / 15.1 GB	646	3
...8 27B Obliterated E03 Bnb 4bit	256K / 17.7 GB	52	1
Qwen3.6 27B Bnb 4bit	256K / 17.7 GB	1194	0
Hemmingway 1	256K / 53.8 GB	10378	838
Qwen3.8 27B OBLITERATED	256K / 83.2 GB	164950	516
OrcaSAQ 2 27B	256K / 12.3 GB	1330	169
JiRackDeltaNet 27b	256K / 10.9 GB	555940	3
Darwin 27B RSI	256K / 53.8 GB	459	14
Qwen3.6 27B OBLITERATED	256K / 53.6 GB	15137	184
...Bonsai 2 27B Heretic Satellite	256K / 53.9 GB	4177	0

Note: green Score (e.g. "73.2") means that the model is better than hotdogs/Qwen3.8-27B-abliterated-AWQ-INT4.