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

Qwen3.8 27B DFlash2 requires approximately 3.9 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 and how large is it?

Qwen3.8 27B DFlash2 is developed by z-lab, 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?

Qwen3.8 27B DFlash2 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 by z-lab — VRAM 3.9GB, 256K context

Name: Qwen3.8 27B DFlash2
Author: z-lab

Qwen3.8 27B DFlash2 is an open-source language model by z-lab. Features: 27b LLM, VRAM: 3.9GB, Context: 256K, License: apache-2.0.

Base model:finetune:qwen/qwen3... Base model:qwen/qwen3.8-27b Block-diffusion Dflash2 Draft-model Qwen3 Region:us Safetensors Sglang Speculative-decoding Vllm

Model Card on HF 🤗: https://huggingface.co/z-lab/Qwen3.8-27B-DFlash2

Qwen3.8 27B DFlash2 Parameters and Internals

LLM Name	Qwen3.8 27B DFlash2
Repository 🤗	https://huggingface.co/z-lab/Qwen3.8-27B-DFlash2
Base Model(s)	Qwen/Qwen3.8-27B Qwen/Qwen3.8-27B
Model Size	27b
Required VRAM	3.9 GB
Updated	2026-08-20
Maintainer	z-lab
Model Type	qwen3
Model Files	3.9 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 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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Qwen3.8 27B DFlash2	256K / 3.9 GB	17062	124