What are the hardware requirements for Qwopus3.8 27B Flash V2 Abliterated?

Qwopus3.8 27B Flash V2 Abliterated requires approximately 54.7 GB of VRAM. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Qwopus3.8 27B Flash V2 Abliterated and how large is it?

Qwopus3.8 27B Flash V2 Abliterated is developed by shawnw3i, 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 Qwopus3.8 27B Flash V2 Abliterated?

Qwopus3.8 27B Flash V2 Abliterated is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Qwopus3.8 27B Flash V2 Abliterated by shawnw3i — VRAM 54.7GB

Name: Qwopus3.8 27B Flash V2 Abliterated
Author: shawnw3i

Qwopus3.8 27B Flash V2 Abliterated is an open-source language model by shawnw3i. Features: 27b LLM, VRAM: 54.7GB, License: apache-2.0, Instruction-Based.

27b Agent Agentic Base model:finetune:jackrong/q... Base model:jackrong/qwopus3.8-... Code-generation Conversational En Endpoints compatible Es Finetuned Function-calling Image-text-to-text Instruct Instruction-tuned Ja Local-inference Mtp Multimodal Qwen Qwen3 Qwen3 5 Reasoning Region:us Ru Safetensors Sharded Speculative-decoding Tensorflow Tool-use Unsloth Vision Zh

Model Card on HF 🤗: https://huggingface.co/shawnw3i/Qwopus3.8-27B-Flash-V2-abliterated

Qwopus3.8 27B Flash V2 Abliterated Parameters and Internals

LLM Name	Qwopus3.8 27B Flash V2 Abliterated
Repository 🤗	https://huggingface.co/shawnw3i/Qwopus3.8-27B-Flash-V2-abliterated
Model Name	/home/llm/.cache/huggingface/hub/models--unsloth--Qwen3.8-27B/snapshots/3ea932cee0a432ae86e9c7826cbe8aef52323a28
Base Model(s)	Jackrong/Qwopus3.8-27B-Flash Jackrong/Qwopus3.8-27B-Flash
Model Size	27b
Required VRAM	54.7 GB
Updated	2026-10-06
Maintainer	shawnw3i
Model Type	qwen3_5
Instruction-Based	Yes
Model Files	2.5 GB: 1-of-12 4.8 GB: 2-of-12 5.0 GB: 3-of-12 4.9 GB: 4-of-12 5.0 GB: 5-of-12 4.9 GB: 6-of-12 4.9 GB: 7-of-12 5.0 GB: 8-of-12 5.0 GB: 9-of-12 4.9 GB: 10-of-12 5.0 GB: 11-of-12 2.8 GB: 12-of-12
Supported Languages	en zh es ru ja
Model Architecture	Qwen3_5ForConditionalGeneration
License	apache-2.0
Model Max Length	262144
Transformers Version	5.17.0
Tokenizer Class	TokenizersBackend
Padding Token	<\|endoftext\|>
Errors	replace

Rank the Qwopus3.8 27B Flash V2 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 Qwopus3.8 27B Flash V2 Abliterated

Best Alternatives	Context / RAM	Downloads	Likes
...27B USS Collective Qx64 Hi Mlx	0K / 21 GB	417	2
Qwopus3.8 27B Flash V2	0K / 55.6 GB	126	17
Tmax 27B	0K / 53.8 GB	4630	26
...en3.8 27B MindMeld Qx64 Hi Mlx	0K / 21 GB	346	1
Qwopus3.8 27B Flash	0K / 55.6 GB	234	19
...en3.8 27B Parapraxis Mxfp8 Mlx	0K / 28.7 GB	206	1
...sion GAIN V1.1 Fable Mxfp8 Mlx	0K / 28.7 GB	720	2
...8 27B Brainwaves WFH Mxfp4 Mlx	0K / 15.1 GB	490	1
Qwen3.8 27B FULL NVFP4	0K / 18.8 GB	336	2
...1 Darker Hero GAIN B Mxfp8 Mlx	0K / 28.7 GB	609	2

Note: green Score (e.g. "73.2") means that the model is better than shawnw3i/Qwopus3.8-27B-Flash-V2-abliterated.