What are the hardware requirements for Qwen1.5 72B Chat GPTQ Int8?

Qwen1.5 72B Chat GPTQ Int8 requires approximately 77 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 72B Chat GPTQ Int8 and how large is it?

Qwen1.5 72B Chat GPTQ Int8 is developed by Qwen, a model with 72b 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 72B Chat GPTQ Int8?

Qwen1.5 72B 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 72B Chat GPTQ Int8 by Qwen — VRAM 77GB, 32K context

Name: Qwen1.5 72B Chat GPTQ Int8
Author: Qwen

Qwen1.5 72B Chat GPTQ Int8 is an open-source language model by Qwen. Features: 72b LLM, VRAM: 77GB, Context: 32K, License: other, Quantized, LLM Explorer Score: 0.11.

Arxiv:2309.16609 8-bit Chat Conversational En Endpoints compatible Gptq Quantized Qwen2 Region:us Safetensors Sharded Tensorflow

Model Card on HF 🤗: https://huggingface.co/Qwen/Qwen1.5-72B-Chat-GPTQ-Int8

Qwen1.5 72B Chat GPTQ Int8 Parameters and Internals

LLM Name	Qwen1.5 72B Chat GPTQ Int8
Repository 🤗	https://huggingface.co/Qwen/Qwen1.5-72B-Chat-GPTQ-Int8
Model Size	72b
Required VRAM	77 GB
Updated	2026-07-05
Maintainer	Qwen
Model Type	qwen2
Model Files	3.9 GB: 1-of-20 4.0 GB: 2-of-20 3.9 GB: 3-of-20 4.0 GB: 4-of-20 4.0 GB: 5-of-20 3.9 GB: 6-of-20 4.0 GB: 7-of-20 3.9 GB: 8-of-20 4.0 GB: 9-of-20 4.0 GB: 10-of-20 3.9 GB: 11-of-20 4.0 GB: 12-of-20 3.9 GB: 13-of-20 4.0 GB: 14-of-20 4.0 GB: 15-of-20 3.9 GB: 16-of-20 4.0 GB: 17-of-20 3.9 GB: 18-of-20 3.3 GB: 19-of-20 2.5 GB: 20-of-20
Supported Languages	en
GPTQ Quantization	Yes
Quantization Type	gptq
Model Architecture	Qwen2ForCausalLM
License	other
Context Length	32768
Model Max Length	32768
Transformers Version	4.37.0
Tokenizer Class	Qwen2Tokenizer
Padding Token	<\|endoftext\|>
Vocabulary Size	152064
Torch Data Type	float16
Errors	replace

Rank the Qwen1.5 72B Chat GPTQ Int8 capabilities

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Instruction Following and Task Automation
Factuality and Completeness of Knowledge
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Data Analysis and Insight Generation
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Best Alternatives to Qwen1.5 72B Chat GPTQ Int8

Best Alternatives	Context / RAM	Downloads	Likes
Kimi Dev 72B GPTQ 4bit	128K / 45.8 GB	12	2
Qwen1.5 72B Chat GPTQ	32K / 45.4 GB	2	1
Qwen2.5 72B Instruct GPTQ Int4	32K / 41.6 GB	48399	44
Qwen2.5 72B Instruct GPTQ Int8	32K / 77 GB	1893	28
Qwen2 72B Instruct GPTQ Int8	32K / 77 GB	1702	15
Qwen1.5 72B Chat GPTQ Int4	32K / 41.3 GB	6267	37
Qwen2 72B Instruct GPTQ Int4	32K / 41.6 GB	96	33
Kimi Dev 72B 4bit DWQ	128K / 40.9 GB	4465	21
Kimi Dev 72B 8bit	128K / 77.1 GB	361	2
Kimi Dev 72B 5bit	128K / 50.1 GB	368	2

Note: green Score (e.g. "73.2") means that the model is better than Qwen/Qwen1.5-72B-Chat-GPTQ-Int8.