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

Qwen3.8 27B JCPTnoarchive requires approximately 55.6 GB of VRAM. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

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

Qwen3.8 27B JCPTnoarchive is developed by otisberg, 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 JCPTnoarchive?

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

Qwen3.8 27B JCPTnoarchive by otisberg — VRAM 55.6GB

Name: Qwen3.8 27B JCPTnoarchive
Author: otisberg

Qwen3.8 27B JCPTnoarchive is an open-source language model by otisberg. Features: 27b LLM, VRAM: 55.6GB, Quantized, LLM Explorer Score: 0.3.

Conversational Endpoints compatible Gguf Llama-cpp Llama.cpp Quantized Qwen3 5 Region:us Safetensors Sharded Tensorflow Unsloth Vision Vision-language-model

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

Qwen3.8 27B JCPTnoarchive Parameters and Internals

LLM Name	Qwen3.8 27B JCPTnoarchive
Repository 🤗	https://huggingface.co/otisberg/Qwen3.8-27B-jCPTnoarchive
Model Name	otisberg/Qwen3.8-27B-jCPTnoarchive
Model Size	27b
Required VRAM	55.6 GB
Updated	2026-10-03
Maintainer	otisberg
Model Type	qwen3_5
Model Files	0.9 GB 16.5 GB 28.6 GB 4.0 GB: 1-of-18 3.0 GB: 2-of-18 2.5 GB: 3-of-18 4.0 GB: 4-of-18 2.1 GB: 5-of-18 4.0 GB: 6-of-18 2.1 GB: 7-of-18 4.0 GB: 8-of-18 2.1 GB: 9-of-18 4.0 GB: 10-of-18 2.1 GB: 11-of-18 4.0 GB: 12-of-18 2.1 GB: 13-of-18 4.0 GB: 14-of-18 2.1 GB: 15-of-18 4.0 GB: 16-of-18 2.1 GB: 17-of-18 3.4 GB: 18-of-18
GGUF Quantization	Yes
Quantization Type	gguf
Model Architecture	Qwen3_5ForConditionalGeneration
Model Max Length	262144
Transformers Version	5.3.0
Tokenizer Class	TokenizersBackend
Padding Token	<\|endoftext\|>
Errors	replace

Rank the Qwen3.8 27B JCPTnoarchive 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

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...N V1.1 NM DAU NEO MAX MTP GGUF	0K / 0.9 GB	489061	325
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...inkingCap Qwen3.8 27B MIX GGUF	0K / 13.4 GB	1395	7
...B Abliterated V2 PQ2 0 MTP MLX	0K / 0.8 GB	1040	2
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...N Blackwell DFlash2 Ultra V1.0	0K / 0.9 GB	3531	3
Ternary Bonsai 2 27B MLX 4bit	0K / 16 GB	1175	2
EleMo V3 Base	0K / 0.9 GB	1989	1
...4 Blackwell DFlash2 Ultra V1.0	0K / 0.9 GB	789	2

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