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

Cyberneurova Qwen3.8 27B requires approximately 0.7 GB of VRAM. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Cyberneurova Qwen3.8 27B and how large is it?

Cyberneurova Qwen3.8 27B is developed by cyberneurova, 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 Cyberneurova Qwen3.8 27B?

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

Cyberneurova Qwen3.8 27B by cyberneurova — VRAM 0.7GB

Name: Cyberneurova Qwen3.8 27B
Author: cyberneurova

Cyberneurova Qwen3.8 27B is an open-source language model by cyberneurova. Features: 27b LLM, VRAM: 0.7GB, License: apache-2.0, LLM Explorer Score: 0.27.

Base model:finetune:qwen/qwen3... Base model:qwen/qwen3.8-27b Conversational Cyberneurova Endpoints compatible Image-text-to-text Qwen3 5 Region:us Safetensors

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

Cyberneurova Qwen3.8 27B Parameters and Internals

LLM Name	Cyberneurova Qwen3.8 27B
Repository 🤗	https://huggingface.co/cyberneurova/cyberneurova-Qwen3.8-27B
Base Model(s)	Qwen/Qwen3.8-27B Qwen/Qwen3.8-27B
Model Size	27b
Required VRAM	0.7 GB
Updated	2026-08-18
Maintainer	cyberneurova
Model Type	qwen3_5
Model Files	0.8 GB 0.8 GB 0.8 GB 0.7 GB 0.8 GB 0.8 GB 0.8 GB 0.7 GB 0.8 GB 0.8 GB 0.8 GB 0.7 GB 0.8 GB 0.8 GB 0.8 GB 0.8 GB 0.7 GB 0.8 GB 0.8 GB 0.8 GB 0.7 GB 0.8 GB 0.8 GB 0.7 GB 0.8 GB 0.7 GB 0.8 GB 0.8 GB 0.8 GB 0.7 GB 0.8 GB 0.8 GB 0.8 GB 0.7 GB 0.8 GB 0.8 GB 0.8 GB 0.8 GB 0.7 GB 0.8 GB 0.8 GB 0.8 GB 0.7 GB 0.8 GB 0.8 GB
Model Architecture	Qwen3_5ForConditionalGeneration
License	apache-2.0
Transformers Version	5.8.0.dev0
Torch Data Type	bfloat16

Rank the Cyberneurova Qwen3.8 27B 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

Quantized Models of the Cyberneurova Qwen3.8 27B

Model	Likes	Downloads	VRAM
Cyberneurova Qwen3.8 27B 8bit	1	347	29 GB

Best Alternatives to Cyberneurova Qwen3.8 27B

Best Alternatives	Context / RAM	Downloads	Likes
...wopus3.8 27B Flash Mlx OQ4e 1M	1024K / 16.9 GB	211	1
Agens Pilot	1024K / 54.7 GB	96	3
Qwen3.8 27B NPU2	256K / GB	252	4
JEV 27B VL	0K / 55.6 GB	1525286	966
Clef	0K / 54.7 GB	19314	2182
Qwen3.6 27B	0K / 55.4 GB	6728138	2197
Qwen3.8 27B	0K / 55.6 GB	2	8753
Qwen3.8 27B	0K / 55.6 GB	2727	21
Qwen3.8 27B MLX	0K / 16 GB	1411	18
Qwen3.8 27B FP8	0K / 0.4 GB	123157	416

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