What are the hardware requirements for Qwen1.5 32B Chat GPTQ Int8?

Qwen1.5 32B Chat GPTQ Int8 requires approximately 34.9 GB of VRAM and supports a context window of 32K tokens. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Qwen1.5 32B Chat GPTQ Int8 and how large is it?

Qwen1.5 32B Chat GPTQ Int8 is developed by study-hjt, a model with 32b 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 Qwen1.5 32B Chat GPTQ Int8?

Qwen1.5 32B Chat GPTQ Int8 is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Qwen1.5 32B Chat GPTQ Int8 by study-hjt — VRAM 34.9GB, 32K context

Name: Qwen1.5 32B Chat GPTQ Int8
Rating: 1 (8 reviews)
Author: study-hjt

Qwen1.5 32B Chat GPTQ Int8 is an open-source language model by study-hjt. Features: 32b LLM, VRAM: 34.9GB, Context: 32K, License: other, Quantized, LLM Explorer Score: 0.12.

Arxiv:2309.16609 32b 8-bit Chat Conversational En Endpoints compatible Gptq Int8 Quantized Qwen Qwen2 Region:us Safetensors Sharded Tensorflow Zh

Model Card on HF 🤗: https://huggingface.co/study-hjt/Qwen1.5-32B-Chat-GPTQ-Int8

Qwen1.5 32B Chat GPTQ Int8 Parameters and Internals

Model Type

text-generation

Additional Notes

Model supports stable 32K context length and has improved multilingual support.

Supported Languages

en (multilingual), zh (multilingual)

Training Details

Methodology:

pretrained on a large amount of data with supervised finetuning and direct preference optimization

Model Architecture:

Transformer architecture with SwiGLU activation, attention QKV bias, group query attention, mixture of sliding window attention and full attention

Input Output

Accepted Modalities:

text

Output Format:

text

Performance Tips:

Use provided hyper-parameters in generation_config.json for better performance in cases like code switching.

LLM Name	Qwen1.5 32B Chat GPTQ Int8
Repository 🤗	https://huggingface.co/study-hjt/Qwen1.5-32B-Chat-GPTQ-Int8
Model Size	32b
Required VRAM	34.9 GB
Updated	2026-08-03
Maintainer	study-hjt
Model Type	qwen2
Model Files	10.0 GB: 1-of-4 10.0 GB: 2-of-4 9.9 GB: 3-of-4 5.0 GB: 4-of-4
Supported Languages	en zh
GPTQ Quantization	Yes
Quantization Type	gptq
Model Architecture	Qwen2ForCausalLM
License	other
Context Length	32768
Model Max Length	32768
Transformers Version	4.39.3
Tokenizer Class	Qwen2Tokenizer
Padding Token	<\|endoftext\|>
Vocabulary Size	152064
Torch Data Type	float16
Errors	replace

Rank the Qwen1.5 32B Chat GPTQ Int8 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 Qwen1.5 32B Chat GPTQ Int8

Best Alternatives	Context / RAM	Downloads	Likes
Qwen2.5 32B Instruct GPTQ Int4	32K / 19.5 GB	478520	40
Qwen2.5 32B Instruct GPTQ Int8	32K / 35.1 GB	121583	14
...5 Coder 32B Instruct GPTQ Int4	32K / 19.5 GB	20619	24
...5 Coder 32B Instruct GPTQ Int8	32K / 35.1 GB	771	24
QwQ 32B Preview GPTQ 4bit	32K / 16.1 GB	306	3
Qwen1.5 32B Chat GPTQ Int4	32K / 19.5 GB	6616	31
Qwen Qwen1.5 32B 4 Bit Gptq	32K / 19.2 GB	8	0
...Logic Mix 3 32B Mlx OptiQ 5bit	128K / 22.3 GB	41	1
...pSeek R1 Distill Qwen 32B 4bit	128K / 18.5 GB	7795	51
Hydraulic Deepseek 16bit	128K / 65.8 GB	52	0

Note: green Score (e.g. "73.2") means that the model is better than study-hjt/Qwen1.5-32B-Chat-GPTQ-Int8.