What are the hardware requirements for Qwen3.8 27B PrismaAQUA 5.5bit Vllm?

Qwen3.8 27B PrismaAQUA 5.5bit Vllm requires approximately 23.5 GB of VRAM. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Qwen3.8 27B PrismaAQUA 5.5bit Vllm and how large is it?

Qwen3.8 27B PrismaAQUA 5.5bit Vllm is developed by rdtand, 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 PrismaAQUA 5.5bit Vllm?

Qwen3.8 27B PrismaAQUA 5.5bit Vllm is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Qwen3.8 27B PrismaAQUA 5.5bit Vllm by rdtand — VRAM 23.5GB

Name: Qwen3.8 27B PrismaAQUA 5.5bit Vllm
Author: rdtand

Qwen3.8 27B PrismaAQUA 5.5bit Vllm is an open-source language model by rdtand. Features: 27b LLM, VRAM: 23.5GB, License: apache-2.0, LLM Explorer Score: 0.38.

Aqua-aura Base model:quantized:qwen/qwen... Base model:qwen/qwen3.8-27b Compressed-tensors Conversational Endpoints compatible Fp8 Image-text-to-text Mixed-precision Nvfp4 Prismaquant Qwen3 5 Region:us Safetensors Sharded Tensorflow Vllm

Model Card on HF 🤗: https://huggingface.co/rdtand/Qwen3.8-27B-PrismaAQUA-5.5bit-vllm

Qwen3.8 27B PrismaAQUA 5.5bit Vllm Parameters and Internals

LLM Name	Qwen3.8 27B PrismaAQUA 5.5bit Vllm
Repository 🤗	https://huggingface.co/rdtand/Qwen3.8-27B-PrismaAQUA-5.5bit-vllm
Base Model(s)	Qwen/Qwen3.8-27B Qwen/Qwen3.8-27B
Model Size	27b
Required VRAM	23.5 GB
Updated	2026-08-15
Maintainer	rdtand
Model Type	qwen3_5
Model Files	5.3 GB: 1-of-5 5.4 GB: 2-of-5 5.3 GB: 3-of-5 5.3 GB: 4-of-5 2.2 GB: 5-of-5
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 PrismaAQUA 5.5bit Vllm capabilities

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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 PrismaAQUA 5.5bit Vllm

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
Qwen3.8 27B NVFP4	0K / 22 GB	30122	14
ThinkingCap Qwen3.6 27B	0K / 54.7 GB	35947	614
Qwen3.8 27B INT8 W8A16 MTP	0K / 30.7 GB	4723	26
Qwen3.6 27B FP8	0K / 0.4 GB	7740472	342
Qwen3.8 27B Heretic Ara	0K / 54.6 GB	841	46
Qwen3.5 27B	0K / 55.2 GB	2536294	1028

Note: green Score (e.g. "73.2") means that the model is better than rdtand/Qwen3.8-27B-PrismaAQUA-5.5bit-vllm.