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

Qwen3.8 27B GGUF requires approximately 0.9 GB of VRAM. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Qwen3.8 27B GGUF and how large is it?

Qwen3.8 27B GGUF is developed by unsloth, 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 GGUF?

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

Qwen3.8 27B GGUF by unsloth — VRAM 0.9GB

Name: Qwen3.8 27B GGUF
Author: unsloth

Qwen3.8 27B GGUF is an open-source language model by unsloth. Features: 27b LLM, VRAM: 0.9GB, License: apache-2.0, Quantized, LLM Explorer Score: 0.45.

Base model:quantized:qwen/qwen... Base model:qwen/qwen3.8-27b Conversational Endpoints compatible Gguf Imatrix Q3 Quantized Qwen3 5 Region:us Unsloth

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

Qwen3.8 27B GGUF Parameters and Internals

LLM Name	Qwen3.8 27B GGUF
Repository 🤗	https://huggingface.co/unsloth/Qwen3.8-27B-GGUF
Base Model(s)	Qwen/Qwen3.8-27B Qwen/Qwen3.8-27B
Model Size	27b
Required VRAM	0.9 GB
Updated	2026-08-14
Maintainer	unsloth
Model Type	qwen3_5
Model Files	16.3 GB 15.7 GB 13.8 GB 12.6 GB 16.1 GB 17.5 GB 17.1 GB 16.1 GB 19.8 GB 19.3 GB 22.9 GB 29.0 GB 10.3 GB 9.0 GB 11.9 GB 10.7 GB 13.4 GB 17.9 GB 20.2 GB 25.9 GB 31.5 GB 0.9 GB 0.9 GB
GGUF Quantization	Yes
Quantization Type	gguf\|q3\|q4_k\|q5_k
Model Architecture	Qwen3_5ForConditionalGeneration
License	apache-2.0
Transformers Version	5.16.0.dev0

Rank the Qwen3.8 27B GGUF 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

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