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

Qwen3.8 27B OBLITERATEDpintus 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 OBLITERATEDpintus and how large is it?

Qwen3.8 27B OBLITERATEDpintus is developed by JACK-POTTSSON, 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 OBLITERATEDpintus?

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

Qwen3.8 27B OBLITERATEDpintus by JACK-POTTSSON — VRAM 83.2GB, 256K context

Name: Qwen3.8 27B OBLITERATEDpintus
Author: JACK-POTTSSON

Qwen3.8 27B OBLITERATEDpintus is an open-source language model by JACK-POTTSSON. Features: 27b LLM, VRAM: 83.2GB, Context: 256K, License: apache-2.0, Quantized, LLM Explorer Score: 0.28.

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/JACK-POTTSSON/Qwen3.8-27B-OBLITERATEDpintus

Qwen3.8 27B OBLITERATEDpintus Parameters and Internals

LLM Name	Qwen3.8 27B OBLITERATEDpintus
Repository 🤗	https://huggingface.co/JACK-POTTSSON/Qwen3.8-27B-OBLITERATEDpintus
Base Model(s)	Qwen/Qwen3.8-27B Qwen/Qwen3.8-27B
Model Size	27b
Required VRAM	83.2 GB
Updated	2026-08-24
Maintainer	JACK-POTTSSON
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

Rank the Qwen3.8 27B OBLITERATEDpintus 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
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Multi-Language Support and Translation

Best Alternatives to Qwen3.8 27B OBLITERATEDpintus

Best Alternatives	Context / RAM	Downloads	Likes
Qwen3.8 27B OBLITERATED	256K / 83.2 GB	164950	516
JiRackDeltaNet 27b	256K / 10.9 GB	556172	3
...Bonsai 2 27B Heretic Satellite	256K / 53.9 GB	4177	0
Veloxy Titan 32B	256K / 53.8 GB	608	0
Qwen3.8 Whittle 16B	256K / 2.4 GB	1719	1
...onsai 27B Mlx Lossless 1.75bpw	0K / 5.9 GB	312	1
...tic Uncensored NM DAU MXFP4 1M	1024K / 0.1 GB	1502	1
...tic Uncensored NM DAU NVFP4 1M	256K / 0.8 GB	4357	2
...Heretic Abliterated Uncensored	256K / 53.9 GB	1891	3
...eretic Uncensored NM DAU NVFP4	256K / 0.1 GB	1767	2

Note: green Score (e.g. "73.2") means that the model is better than JACK-POTTSSON/Qwen3.8-27B-OBLITERATEDpintus.