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

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

Qwen3.8 27B MIX GGUF is developed by vmarcelo, 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 MIX GGUF?

Qwen3.8 27B MIX 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 MIX GGUF by vmarcelo — VRAM 0.9GB

Name: Qwen3.8 27B MIX GGUF
Author: vmarcelo

Qwen3.8 27B MIX GGUF is an open-source language model by vmarcelo. Features: 27b LLM, VRAM: 0.9GB, License: other, Quantized, LLM Explorer Score: 0.33.

Base model:quantized:qwen/qwen... Base model:qwen/qwen3.8-27b-fp... Conversational Endpoints compatible Gguf Imatrix Multilingual Multimodal Quantized Qwen3.5 Qwen3 5 Region:us Vision Vulkan

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

Qwen3.8 27B MIX GGUF Parameters and Internals

LLM Name	Qwen3.8 27B MIX GGUF
Repository 🤗	https://huggingface.co/vmarcelo/Qwen3.8-27B-MIX_GGUF
Base Model(s)	Qwen/Qwen3.8-27B-FP8 Qwen/Qwen3.8-27B-FP8
Model Size	27b
Required VRAM	0.9 GB
Updated	2026-08-15
Maintainer	vmarcelo
Model Type	qwen3_5
Model Files	12.6 GB 14.1 GB 0.9 GB
GGUF Quantization	Yes
Quantization Type	gguf
Model Architecture	Qwen3_5ForConditionalGeneration
License	other
Transformers Version	5.16.0.dev0

Rank the Qwen3.8 27B MIX 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 MIX GGUF

Best Alternatives	Context / RAM	Downloads	Likes
Qwen3.8 27B GGUF	0K / 0.9 GB	0	685
...en3.8 27B PristinelyUncensored	0K / 55.5 GB	2244	5
... Opus Reasoning Distilled GGUF	0K / 0.9 GB	67921	679
... Opus Reasoning Distilled GGUF	0K / 10.7 GB	9907	48
...i 27B MLX BF16 Config Repaired	0K / 53.5 GB	678	0
Qwen3.6 27B OptiQ 4bit	256K / 18.7 GB	13065	59
Bonsai 27B Mlx 1bit	0K / 5.1 GB	809309	205
Qwen3.8 27B 4bit	0K / 16 GB	6055	27
Ternary Bonsai 27B Mlx 2bit	0K / 8.5 GB	809024	168
Qwen3.8 27B MLX 4bit	0K / 16 GB	19712	10

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