What are the hardware requirements for Qwen3.8 27B JANG 4S?

Qwen3.8 27B JANG 4S requires approximately 17.2 GB of VRAM. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Qwen3.8 27B JANG 4S and how large is it?

Qwen3.8 27B JANG 4S 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 4S?

Qwen3.8 27B JANG 4S 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 4S by Chungulus — VRAM 17.2GB

Name: Qwen3.8 27B JANG 4S
Author: Chungulus

Qwen3.8 27B JANG 4S is an open-source language model by Chungulus. Features: 27b LLM, VRAM: 17.2GB, 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_4S

Qwen3.8 27B JANG 4S Parameters and Internals

LLM Name	Qwen3.8 27B JANG 4S
Repository 🤗	https://huggingface.co/Chungulus/Qwen3.8-27B-JANG_4S
Base Model(s)	Qwen/Qwen3.8-27B Qwen/Qwen3.8-27B
Model Size	27b
Required VRAM	17.2 GB
Updated	2026-08-17
Maintainer	Chungulus
Model Type	qwen3_5
Model Files	0.5 GB: 1-of-28 0.6 GB: 2-of-28 0.5 GB: 3-of-28 0.8 GB: 4-of-28 0.6 GB: 5-of-28 0.5 GB: 6-of-28 0.6 GB: 7-of-28 0.5 GB: 8-of-28 0.6 GB: 9-of-28 0.5 GB: 10-of-28 0.6 GB: 11-of-28 0.5 GB: 12-of-28 0.6 GB: 13-of-28 0.6 GB: 14-of-28 0.5 GB: 15-of-28 0.6 GB: 16-of-28 0.6 GB: 17-of-28 0.5 GB: 18-of-28 0.6 GB: 19-of-28 0.5 GB: 20-of-28 0.6 GB: 21-of-28 0.6 GB: 22-of-28 0.5 GB: 23-of-28 0.6 GB: 24-of-28 0.6 GB: 25-of-28 0.5 GB: 26-of-28 1.3 GB: 27-of-28 1.2 GB: 28-of-28
Model Architecture	Qwen3_5ForConditionalGeneration
License	apache-2.0
Model Max Length	262144
Transformers Version	5.8.0.dev0
Tokenizer Class	Qwen2Tokenizer
Padding Token	<\|endoftext\|>
Errors	replace

Rank the Qwen3.8 27B JANG 4S 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 4S

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_4S.