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

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

Qwen3.8 27B MagicQuant GGUF is developed by magiccodingman, 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 MagicQuant GGUF?

Qwen3.8 27B MagicQuant 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 MagicQuant GGUF by magiccodingman — VRAM 0.9GB

Name: Qwen3.8 27B MagicQuant GGUF
Author: magiccodingman

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

Base model:quantized:qwen/qwen... Base model:qwen/qwen3.8-27b Conversational Endpoints compatible Gguf Imatrix Magicquant Q8 Quantized Qwen3 5 Region:us Safetensors

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

Qwen3.8 27B MagicQuant GGUF Parameters and Internals

LLM Name	Qwen3.8 27B MagicQuant GGUF
Repository 🤗	https://huggingface.co/magiccodingman/Qwen3.8-27B-MagicQuant-GGUF
Base Model(s)	Qwen/Qwen3.8-27B Qwen/Qwen3.8-27B
Model Size	27b
Required VRAM	0.9 GB
Updated	2026-08-17
Maintainer	magiccodingman
Model Type	qwen3_5
Model Files	29.0 GB 12.0 GB 10.8 GB 17.1 GB 16.3 GB 18.1 GB 20.4 GB 25.9 GB 23.2 GB 9.1 GB 13.5 GB 0.9 GB
GGUF Quantization	Yes
Quantization Type	gguf\|q8\|q4_k\|q5_k
Model Architecture	Qwen3_5ForConditionalGeneration
License	apache-2.0
Model Max Length	262144
Transformers Version	5.8.0.dev0
Tokenizer Class	Qwen2Tokenizer
Padding Token	<\|endoftext\|>
Errors	replace

Rank the Qwen3.8 27B MagicQuant GGUF 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 Qwen3.8 27B MagicQuant GGUF

Best Alternatives	Context / RAM	Downloads	Likes
Qwen3.8 27B GGUF	0K / 0.9 GB	0	685
... Opus Reasoning Distilled GGUF	0K / 0.9 GB	67921	679
...en3.8 27B PristinelyUncensored	0K / 55.5 GB	2244	5
Qwen3.8 27B MIX GGUF	0K / 0.9 GB	141	3
... Opus Reasoning Distilled GGUF	0K / 10.7 GB	9907	48
...i 27B MLX BF16 Config Repaired	0K / 53.5 GB	678	0
...n3.8 27B Heretic Ara Q6 K GGUF	0K / 22.4 GB	1695	1
Qwen3.6 27B OptiQ 4bit	256K / 18.7 GB	13065	59
Bonsai 27B Mlx 1bit	0K / 5.1 GB	809309	205
Qwen3.8 27B 8bit	0K / 29.4 GB	13892	33

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