What are the hardware requirements for Qwen3.8 27B Fable Distill Mlx 8Bit?

Qwen3.8 27B Fable Distill Mlx 8Bit requires approximately 28.4 GB of VRAM. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Qwen3.8 27B Fable Distill Mlx 8Bit and how large is it?

Qwen3.8 27B Fable Distill Mlx 8Bit is developed by McG-221, 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 Fable Distill Mlx 8Bit?

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

Qwen3.8 27B Fable Distill Mlx 8Bit by McG-221 — VRAM 28.4GB

Name: Qwen3.8 27B Fable Distill Mlx 8Bit
Author: McG-221

Qwen3.8 27B Fable Distill Mlx 8Bit is an open-source language model by McG-221. Features: 27b LLM, VRAM: 28.4GB, License: apache-2.0, Quantized, LLM Explorer Score: 0.31.

8-bit 8bit Base model:quantized:teichai/q... Base model:teichai/qwen3.8-27b... Conversational Dataset:armand0e/claude-fable-... Dataset:armand0e/fable-5-chat En Endpoints compatible Image-text-to-text Mlx Mlx-my-repo Quantized Qwen3 5 Region:us Safetensors Sharded Tensorflow Unsloth

Model Card on HF 🤗: https://huggingface.co/McG-221/Qwen3.8-27B-Fable-Distill-mlx-8Bit

Qwen3.8 27B Fable Distill Mlx 8Bit Parameters and Internals

LLM Name	Qwen3.8 27B Fable Distill Mlx 8Bit
Repository 🤗	https://huggingface.co/McG-221/Qwen3.8-27B-Fable-Distill-mlx-8Bit
Model Name	unsloth/Qwen3.8-27B
Base Model(s)	TeichAI/Qwen3.8-27B-Fable-Distill TeichAI/Qwen3.8-27B-Fable-Distill
Model Size	27b
Required VRAM	28.4 GB
Updated	2026-08-22
Maintainer	McG-221
Model Type	qwen3_5
Model Files	5.3 GB: 1-of-6 5.3 GB: 2-of-6 5.3 GB: 3-of-6 5.3 GB: 4-of-6 5.3 GB: 5-of-6 1.9 GB: 6-of-6
Supported Languages	en
Quantization Type	8bit
Model Architecture	Qwen3_5ForConditionalGeneration
License	apache-2.0
Model Max Length	262144
Tokenizer Class	TokenizersBackend
Padding Token	<\|endoftext\|>
Torch Data Type	bfloat16
Errors	replace

Rank the Qwen3.8 27B Fable Distill Mlx 8Bit 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 Fable Distill Mlx 8Bit

Best Alternatives	Context / RAM	Downloads	Likes
Qwen3.6 27B OptiQ 4bit	256K / 18.7 GB	13065	59
Bonsai 27B Mlx 1bit	0K / 5.1 GB	809309	205
Ternary Bonsai 27B Mlx 2bit	0K / 8.5 GB	809024	168
Qwen3.8 27B 8bit	0K / 29.4 GB	13892	33
Qwen3.8 27B 4bit	0K / 16 GB	6055	27
Qwen3.8 27B MLX 4bit	0K / 16 GB	19712	10
Qwen3.8 27B MLX 8bit	0K / 29.4 GB	24811	7
Qwen3.6 27B MLX 8bit	0K / 29.4 GB	879145	14
Qwen3.6 27B MLX 6bit	0K / 22.7 GB	812977	2
Qwen3.8 27B OptiQ 4bit	0K / 19.4 GB	3189	9

Note: green Score (e.g. "73.2") means that the model is better than McG-221/Qwen3.8-27B-Fable-Distill-mlx-8Bit.