What are the hardware requirements for Qwen3.8 27B AWQ BF16 INT8?

Qwen3.8 27B AWQ BF16 INT8 requires approximately 36.4 GB of VRAM. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Qwen3.8 27B AWQ BF16 INT8 and how large is it?

Qwen3.8 27B AWQ BF16 INT8 is developed by utrominon, 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 AWQ BF16 INT8?

Qwen3.8 27B AWQ BF16 INT8 is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Qwen3.8 27B AWQ BF16 INT8 by utrominon — VRAM 36.4GB

Name: Qwen3.8 27B AWQ BF16 INT8
Author: utrominon

Qwen3.8 27B AWQ BF16 INT8 is an open-source language model by utrominon. Features: 27b LLM, VRAM: 36.4GB, License: apache-2.0, Quantized, LLM Explorer Score: 0.29.

Awq Base model:quantized:qwen/qwen... Base model:qwen/qwen3.8-27b Compressed-tensors Conversational En Endpoints compatible Gptq Image-text-to-text Int8 Quantized Qwen3 5 Region:us Ru Safetensors Sharded Tensorflow Vllm W8a16

Model Card on HF 🤗: https://huggingface.co/utrominon/Qwen3.8-27B-AWQ-BF16-INT8

Qwen3.8 27B AWQ BF16 INT8 Parameters and Internals

LLM Name	Qwen3.8 27B AWQ BF16 INT8
Repository 🤗	https://huggingface.co/utrominon/Qwen3.8-27B-AWQ-BF16-INT8
Base Model(s)	Qwen/Qwen3.8-27B Qwen/Qwen3.8-27B
Model Size	27b
Required VRAM	36.4 GB
Updated	2026-08-27
Maintainer	utrominon
Model Type	qwen3_5
Model Files	20.0 GB: 1-of-2 16.4 GB: 2-of-2 0.8 GB
Supported Languages	en ru
AWQ Quantization	Yes
Quantization Type	awq
Model Architecture	Qwen3_5ForConditionalGeneration
License	apache-2.0
Model Max Length	262144
Transformers Version	5.15.1
Tokenizer Class	Qwen2Tokenizer
Padding Token	<\|endoftext\|>
Errors	replace

Rank the Qwen3.8 27B AWQ BF16 INT8 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 AWQ BF16 INT8

Best Alternatives	Context / RAM	Downloads	Likes
Qwen3.8 27B AWQ INT4	0K / 21 GB	21015	32
Qwen3.6 27B AWQ INT4	0K / 20.4 GB	2563390	103
Qwen3.6 27B AWQ	0K / 22 GB	668924	24
Qwen3.8 27B AWQ 4bit	0K / 27.7 GB	11874	6
Qwen3.6 27B AWQ BF16 INT4	0K / 28.3 GB	419171	41
Qwen3.8 27B AWQ 5.0bpw	0K / 17.3 GB	1445	20
Qwen3.8 27B AWQ BF16 INT4	0K / 28.8 GB	1571	11
...wen3.6 27B Abliterated AWQ MTP	0K / 18.4 GB	244978	12
Qwen3.8 27B W4A16 AWQ	0K / 0.8 GB	3413	7
Qwen3.5 27B AWQ 4bit	0K / 20 GB	279064	42

Note: green Score (e.g. "73.2") means that the model is better than utrominon/Qwen3.8-27B-AWQ-BF16-INT8.