What are the hardware requirements for Qwen3.8 27B OBLITERATED?

Qwen3.8 27B OBLITERATED requires approximately 83.2 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 OBLITERATED and how large is it?

Qwen3.8 27B OBLITERATED is developed by OBLITERATUS, 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 OBLITERATED?

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

Qwen3.8 27B OBLITERATED by OBLITERATUS — VRAM 83.2GB, 256K context

Name: Qwen3.8 27B OBLITERATED
Author: OBLITERATUS

Qwen3.8 27B OBLITERATED is an open-source language model by OBLITERATUS. Features: 27b LLM, VRAM: 83.2GB, Context: 256K, License: apache-2.0, Quantized, LLM Explorer Score: 0.57.

Abliterated Ai-safety-research Base model:quantized:qwen/qwen... Base model:qwen/qwen3.8-27b Conversational Endpoints compatible Gguf Mlx Obliteratus Q4 Quantized Qwen3 Qwen3.8 Qwen3 5 text Red-team Region:us Safetensors Sharded Tensorflow Uncensored

Model Card on HF 🤗: https://huggingface.co/OBLITERATUS/Qwen3.8-27B-OBLITERATED

Qwen3.8 27B OBLITERATED Parameters and Internals

LLM Name	Qwen3.8 27B OBLITERATED
Repository 🤗	https://huggingface.co/OBLITERATUS/Qwen3.8-27B-OBLITERATED
Base Model(s)	Qwen/Qwen3.8-27B Qwen/Qwen3.8-27B
Model Size	27b
Required VRAM	83.2 GB
Updated	2026-08-22
Maintainer	OBLITERATUS
Model Type	qwen3_5_text
Model Files	15.4 GB 16.8 GB 19.5 GB 22.4 GB 29.0 GB 0.9 GB 4.0 GB: 1-of-18 2.5 GB: 1-of-28 3.0 GB: 2-of-18 1.9 GB: 2-of-28 2.5 GB: 3-of-18 1.9 GB: 3-of-28 4.0 GB: 4-of-18 1.9 GB: 4-of-28 2.1 GB: 5-of-18 1.9 GB: 5-of-28 4.0 GB: 6-of-18 1.9 GB: 6-of-28 2.1 GB: 7-of-18 1.9 GB: 7-of-28 4.0 GB: 8-of-18 1.9 GB: 8-of-28 2.1 GB: 9-of-18 1.9 GB: 9-of-28 4.0 GB: 10-of-18 1.9 GB: 10-of-28 2.1 GB: 11-of-18 1.9 GB: 11-of-28 4.0 GB: 12-of-18 1.9 GB: 12-of-28 2.1 GB: 13-of-18 1.9 GB: 13-of-28 4.0 GB: 14-of-18 1.9 GB: 14-of-28 2.1 GB: 15-of-18 1.9 GB: 15-of-28 4.0 GB: 16-of-18 1.9 GB: 16-of-28 2.1 GB: 17-of-18
GGUF Quantization	Yes
Quantization Type	q4\|gguf\|q4_k\|q5_k
Model Architecture	Qwen3_5ForCausalLM
License	apache-2.0
Context Length	262144
Model Max Length	262144
Transformers Version	5.12.0
Vocabulary Size	248320

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