What are the hardware requirements for Qwen3.8 27B JANG 6M?

Qwen3.8 27B JANG 6M requires approximately 24.3 GB of VRAM. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Qwen3.8 27B JANG 6M and how large is it?

Qwen3.8 27B JANG 6M is developed by Chungulus, 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 JANG 6M?

Qwen3.8 27B JANG 6M is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Qwen3.8 27B JANG 6M by Chungulus — VRAM 24.3GB

Name: Qwen3.8 27B JANG 6M
Author: Chungulus

Qwen3.8 27B JANG 6M is an open-source language model by Chungulus. Features: 27b LLM, VRAM: 24.3GB, License: apache-2.0.

Base model:quantized:qwen/qwen... Base model:qwen/qwen3.8-27b Conversational Image-text-to-text Mtp Quantized Qwen3.8 Qwen3 5 Region:us Safetensors Sharded Tensorflow Vision Vision-language

Model Card on HF 🤗: https://huggingface.co/Chungulus/Qwen3.8-27B-JANG_6M

Qwen3.8 27B JANG 6M Parameters and Internals

LLM Name	Qwen3.8 27B JANG 6M
Repository 🤗	https://huggingface.co/Chungulus/Qwen3.8-27B-JANG_6M
Base Model(s)	Qwen/Qwen3.8-27B Qwen/Qwen3.8-27B
Model Size	27b
Required VRAM	24.3 GB
Updated	2026-08-17
Maintainer	Chungulus
Model Type	qwen3_5
Model Files	0.6 GB: 1-of-39 0.5 GB: 2-of-39 0.5 GB: 3-of-39 0.6 GB: 4-of-39 1.4 GB: 5-of-39 0.5 GB: 6-of-39 0.6 GB: 7-of-39 0.5 GB: 8-of-39 0.6 GB: 9-of-39 0.6 GB: 10-of-39 0.6 GB: 11-of-39 0.5 GB: 12-of-39 0.6 GB: 13-of-39 0.5 GB: 14-of-39 0.6 GB: 15-of-39 0.5 GB: 16-of-39 0.6 GB: 17-of-39 0.6 GB: 18-of-39 0.6 GB: 19-of-39 0.5 GB: 20-of-39 0.6 GB: 21-of-39 0.6 GB: 22-of-39 0.5 GB: 23-of-39 0.5 GB: 24-of-39 0.6 GB: 25-of-39 0.6 GB: 26-of-39 0.6 GB: 27-of-39 0.5 GB: 28-of-39 0.6 GB: 29-of-39 0.5 GB: 30-of-39 0.6 GB: 31-of-39 0.5 GB: 32-of-39 0.6 GB: 33-of-39 0.6 GB: 34-of-39 0.6 GB: 35-of-39 0.5 GB: 36-of-39 0.6 GB: 37-of-39 1.4 GB: 38-of-39 1.3 GB: 39-of-39
Model Architecture	Qwen3_5ForConditionalGeneration
License	apache-2.0
Transformers Version	5.8.0.dev0

Rank the Qwen3.8 27B JANG 6M 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 JANG 6M

Best Alternatives	Context / RAM	Downloads	Likes
Qwen3.8 27B FP8	0K / 0.4 GB	123157	416
Qwen3.8 27B	0K / 55.6 GB	2	8753
Qwen3.6 27B	0K / 55.4 GB	6728138	2197
Qwen3.6 27B NVFP4	0K / 22 GB	1887525	419
...n3.8 27B MTPLX Optimized Speed	0K / 19.6 GB	6989	50
ThinkingCap Qwen3.6 27B	0K / 54.7 GB	35947	614
Qwen3.6 27B FP8	0K / 0.4 GB	7740472	342
Qwen3.5 27B	0K / 55.2 GB	2536294	1028
Qwen3.5 27B	0K / 55.2 GB	8115	16
Qwen3.8 27B NVFP4	0K / 22 GB	30122	14

Note: green Score (e.g. "73.2") means that the model is better than Chungulus/Qwen3.8-27B-JANG_6M.