What are the hardware requirements for Qwenseek 3.8 27B CyberLite BF16?

Qwenseek 3.8 27B CyberLite BF16 requires approximately 54.7 GB of VRAM. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Qwenseek 3.8 27B CyberLite BF16 and how large is it?

Qwenseek 3.8 27B CyberLite BF16 is developed by trjxter, 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 Qwenseek 3.8 27B CyberLite BF16?

Qwenseek 3.8 27B CyberLite BF16 is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Qwenseek 3.8 27B CyberLite BF16 by trjxter — VRAM 54.7GB

Name: Qwenseek 3.8 27B CyberLite BF16
Author: trjxter

Qwenseek 3.8 27B CyberLite BF16 is an open-source language model by trjxter. Features: 27b LLM, VRAM: 54.7GB, License: apache-2.0, LLM Explorer Score: 0.34.

Agentic Base model:adapter:unsloth/qwe... Base model:unsloth/qwen3.8-27b Bf16 Code Controlled-red-team Conversational Cybersecurity Dataset:trjxter/deepseek-v4-fl... Dataset:trjxter/deepseek-v4-pr... Defensive-security En Endpoints compatible Image-text-to-text Lora Qlora Qwen3.8 Qwen3 5 Reasoning Region:us Safetensors Sft Sharded Software-engineering Teacher-distillation Tensorflow Tool-calling Unsloth

Model Card on HF 🤗: https://huggingface.co/trjxter/Qwenseek-3.8-27B-CyberLite-BF16

Qwenseek 3.8 27B CyberLite BF16 Parameters and Internals

LLM Name	Qwenseek 3.8 27B CyberLite BF16
Repository 🤗	https://huggingface.co/trjxter/Qwenseek-3.8-27B-CyberLite-BF16
Model Name	unsloth/Qwen3.8-27B
Base Model(s)	unsloth/Qwen3.8-27B unsloth/Qwen3.8-27B
Model Size	27b
Required VRAM	54.7 GB
Updated	2026-09-01
Maintainer	trjxter
Model Type	qwen3_5
Model Files	2.5 GB: 1-of-12 4.8 GB: 2-of-12 5.0 GB: 3-of-12 4.9 GB: 4-of-12 5.0 GB: 5-of-12 4.9 GB: 6-of-12 4.9 GB: 7-of-12 5.0 GB: 8-of-12 5.0 GB: 9-of-12 4.9 GB: 10-of-12 5.0 GB: 11-of-12 2.8 GB: 12-of-12 0.8 GB
Supported Languages	en
Model Architecture	Qwen3_5ForConditionalGeneration
License	apache-2.0
Model Max Length	262144
Transformers Version	5.5.0
Tokenizer Class	TokenizersBackend
Padding Token	<\|endoftext\|>
Errors	replace

Rank the Qwenseek 3.8 27B CyberLite BF16 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 Qwenseek 3.8 27B CyberLite BF16

Best Alternatives	Context / RAM	Downloads	Likes
Agens Pilot	1024K / 54.7 GB	61	1
Qwen3.8 27B MLX	0K / 16 GB	1411	18
Qwen3.6 27B	0K / 55.4 GB	6728138	2197
Qwen3.8 27B FP8	0K / 0.4 GB	123157	416
Qwen3.8 27B	0K / 55.6 GB	2727	21
Qwen3.8 27B	0K / 55.6 GB	2	8753
Qwen3.6 27B NVFP4	0K / 22 GB	1887525	419
Qwen3.6 27B FP8	0K / 0.4 GB	7740472	342
ThinkingCap Qwen3.6 27B	0K / 54.7 GB	35947	614
Qwen3.5 27B	0K / 55.2 GB	2536294	1028

Note: green Score (e.g. "73.2") means that the model is better than trjxter/Qwenseek-3.8-27B-CyberLite-BF16.