What are the hardware requirements for Qwen3.8 27B DFlash2 EXL3 5.0bpw?

Qwen3.8 27B DFlash2 EXL3 5.0bpw requires approximately 1.5 GB of VRAM and supports a context window of 256K tokens. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Qwen3.8 27B DFlash2 EXL3 5.0bpw and how large is it?

Qwen3.8 27B DFlash2 EXL3 5.0bpw is developed by Mia-AiLab, 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 DFlash2 EXL3 5.0bpw?

Qwen3.8 27B DFlash2 EXL3 5.0bpw is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Qwen3.8 27B DFlash2 EXL3 5.0bpw by Mia-AiLab — VRAM 1.5GB, 256K context

Name: Qwen3.8 27B DFlash2 EXL3 5.0bpw
Author: Mia-AiLab

Qwen3.8 27B DFlash2 EXL3 5.0bpw is an open-source language model by Mia-AiLab. Features: 27b LLM, VRAM: 1.5GB, Context: 256K, License: apache-2.0, LLM Explorer Score: 0.3.

5-bit Base model:quantized:qwen/qwen... Base model:qwen/qwen3.8-27b Block-diffusion Dflash2 Draft-model Exl3 Exllamav3 Qwen3 Region:us Safetensors Speculative-decoding

Model Card on HF 🤗: https://huggingface.co/Mia-AiLab/Qwen3.8-27B-DFlash2-EXL3-5.0bpw

Qwen3.8 27B DFlash2 EXL3 5.0bpw Parameters and Internals

LLM Name	Qwen3.8 27B DFlash2 EXL3 5.0bpw
Repository 🤗	https://huggingface.co/Mia-AiLab/Qwen3.8-27B-DFlash2-EXL3-5.0bpw
Base Model(s)	incoai/Qwen3.8-27B-DFlash2 Qwen/Qwen3.8-27B incoai/Qwen3.8-27B-DFlash2 Qwen/Qwen3.8-27B
Model Size	27b
Required VRAM	1.5 GB
Updated	2026-09-04
Maintainer	Mia-AiLab
Model Type	qwen3
Model Files	1.5 GB
Model Architecture	DFlash2DraftModel
License	apache-2.0
Context Length	262144
Model Max Length	262144
Transformers Version	5.15.0
Vocabulary Size	248320

Rank the Qwen3.8 27B DFlash2 EXL3 5.0bpw 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 DFlash2 EXL3 5.0bpw

Best Alternatives	Context / RAM	Downloads	Likes
Qwen3.8 27B DFlash2	256K / 3.9 GB	17062	124
Qwen3.8 27B DFlash2	256K / 3.9 GB	12235	148
...en3.8 27B DFlash2 EXL3 4.00bpw	256K / 1.2 GB	388	2
Qwen3.8 27B DFlash2 Memra	256K / 3.9 GB	1476	2
Qwen3.8 27B DFlash2 Memra	256K / 3.9 GB	831	1
...wen3.8 27B Heretic Ara DFlash2	256K / 3.9 GB	371	1
Qwen3.8 27B DFlash2 Exp	0K / 3.9 GB	419	1
Qwen3.8 27B DFlash2 FP16	256K / 3.9 GB	242	1

Note: green Score (e.g. "73.2") means that the model is better than Mia-AiLab/Qwen3.8-27B-DFlash2-EXL3-5.0bpw.