What are the hardware requirements for Qwen3.6 27B OBLITERATED?

Qwen3.6 27B OBLITERATED requires approximately 53.6 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 Qwen3.6 27B OBLITERATED and how large is it?

Qwen3.6 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 Qwen3.6 27B OBLITERATED?

Qwen3.6 27B OBLITERATED is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Qwen3.6 27B OBLITERATED by OBLITERATUS — VRAM 53.6GB, 256K context

Name: Qwen3.6 27B OBLITERATED
Author: OBLITERATUS

Qwen3.6 27B OBLITERATED is an open-source language model by OBLITERATUS. Features: 27b LLM, VRAM: 53.6GB, Context: 256K, License: apache-2.0, LLM Explorer Score: 0.34.

Base model:quantized:qwen/qwen... Base model:qwen/qwen3.6-27b Conversational Endpoints compatible Gguf Llama.cpp Lm-studio Obliteratus Ollama Qwen Qwen3 Qwen3.6 Qwen3 5 text Red-team Refusal-analysis Region:us Safetensors Sharded Tensorflow

Model Card on HF 🤗: https://huggingface.co/OBLITERATUS/Qwen3.6-27B-OBLITERATED

Qwen3.6 27B OBLITERATED Parameters and Internals

LLM Name	Qwen3.6 27B OBLITERATED
Repository 🤗	https://huggingface.co/OBLITERATUS/Qwen3.6-27B-OBLITERATED
Base Model(s)	Qwen/Qwen3.6-27B Qwen/Qwen3.6-27B
Model Size	27b
Required VRAM	53.6 GB
Updated	2026-07-22
Maintainer	OBLITERATUS
Model Type	qwen3_5_text
Model Files	2.5 GB: 1-of-28 1.9 GB: 2-of-28 1.9 GB: 3-of-28 1.9 GB: 4-of-28 1.9 GB: 5-of-28 1.9 GB: 6-of-28 1.9 GB: 7-of-28 1.9 GB: 8-of-28 1.9 GB: 9-of-28 1.9 GB: 10-of-28 1.9 GB: 11-of-28 1.9 GB: 12-of-28 1.9 GB: 13-of-28 1.9 GB: 14-of-28 1.9 GB: 15-of-28 1.9 GB: 16-of-28 1.9 GB: 17-of-28 1.9 GB: 18-of-28 1.9 GB: 19-of-28 1.9 GB: 20-of-28 1.9 GB: 21-of-28 1.9 GB: 22-of-28 1.9 GB: 23-of-28 1.9 GB: 24-of-28 1.9 GB: 25-of-28 1.9 GB: 26-of-28 2.5 GB: 27-of-28 1.1 GB: 28-of-28
Model Architecture	Qwen3_5ForCausalLM
License	apache-2.0
Context Length	262144
Model Max Length	262144
Transformers Version	5.8.0
Tokenizer Class	Qwen2Tokenizer
Padding Token	<\|endoftext\|>
Vocabulary Size	248320
Torch Data Type	bfloat16
Errors	replace

Rank the Qwen3.6 27B OBLITERATED 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

Quantized Models of the Qwen3.6 27B OBLITERATED

Model	Likes	Downloads	VRAM
...en3.6 27B OBLITERATED MLX 4bit	3	646	15 GB

Best Alternatives to Qwen3.6 27B OBLITERATED

Best Alternatives	Context / RAM	Downloads	Likes
Qwen3.8 27B Obliterated E03	256K / 53.6 GB	708	1
Sharona Q27B R CodeSecurity V2	256K / 53.8 GB	574	1
Barcenas Qwen3.8 27B Fable	256K / 54.1 GB	869	5
...maAQUA Gridbook 13GB 5080 Vllm	256K / 13 GB	731	4
...wen3.8 P44w75 16.8B Unrepaired	256K / 2.4 GB	929	1
...2 Abliterated OptiQ 3.7bpw Mlx	256K / 13.4 GB	6727	14
...n3.8 27B PrismaScout AQUA 20GB	256K / 20.2 GB	266	3
Qwen3.8 27B Abliteratex	256K / 53.9 GB	321	6
...2 Abliterated OptiQ 3.7bpw Mlx	256K / 13.4 GB	5919	14
Focus Red	256K / 53.8 GB	416	1