What are the hardware requirements for Qwen2 72B Instruct AWQ GEMM?

Qwen2 72B Instruct AWQ GEMM requires approximately 41.6 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 Qwen2 72B Instruct AWQ GEMM and how large is it?

Qwen2 72B Instruct AWQ GEMM is developed by erickbp, 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 Qwen2 72B Instruct AWQ GEMM?

Qwen2 72B Instruct AWQ GEMM is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Qwen2 72B Instruct AWQ GEMM by erickbp — VRAM 41.6GB, 32K context

Name: Qwen2 72B Instruct AWQ GEMM
Author: erickbp

Qwen2 72B Instruct AWQ GEMM is an open-source language model by erickbp. Features: 72b LLM, VRAM: 41.6GB, Context: 32K, License: other, Quantized, Instruction-Based, LLM Explorer Score: 0.13.

Arxiv:2309.00071 4-bit Awq Chat Conversational En Endpoints compatible Instruct Quantized Qwen2 Region:us Safetensors Sharded Tensorflow

Model Card on HF 🤗: https://huggingface.co/erickbp/Qwen2-72B-Instruct-AWQ-GEMM

Qwen2 72B Instruct AWQ GEMM Parameters and Internals

Model Type

text-generation

Training Details

Methodology:

Pretrained with a large amount of data, post-trained with both supervised finetuning and direct preference optimization.

Context Length:

131072

Model Architecture:

Transformer with SwiGLU activation, attention QKV bias, group query attention, etc.

LLM Name	Qwen2 72B Instruct AWQ GEMM
Repository 🤗	https://huggingface.co/erickbp/Qwen2-72B-Instruct-AWQ-GEMM
Model Size	72b
Required VRAM	41.6 GB
Updated	2026-06-06
Maintainer	erickbp
Model Type	qwen2
Instruction-Based	Yes
Model Files	3.9 GB: 1-of-11 3.9 GB: 2-of-11 4.0 GB: 3-of-11 4.0 GB: 4-of-11 3.9 GB: 5-of-11 4.0 GB: 6-of-11 4.0 GB: 7-of-11 3.9 GB: 8-of-11 4.0 GB: 9-of-11 3.5 GB: 10-of-11 2.5 GB: 11-of-11
Supported Languages	en
AWQ Quantization	Yes
Quantization Type	awq
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 Qwen2 72B Instruct AWQ GEMM 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 Qwen2 72B Instruct AWQ GEMM

Best Alternatives	Context / RAM	Downloads	Likes
Qwen2.5 72B Instruct AWQ	32K / 41.6 GB	1054752	78
Athene V2 Chat AWQ	32K / 41.6 GB	64	4
Qwen2 72B Instruct AWQ	32K / 41.6 GB	1612	41
Typhoon V1.5 72B Instruct AWQ	32K / 41.3 GB	11	3
Typhoon V1.5 72B Instruct AWQ	32K / 41.3 GB	5	3
...B Instruct 2.0bpw H Novel EXL2	125K / 23 GB	4	1
Qwen2 72B Instruct 4bit	32K / 40.9 GB	56	2
ECE ILAB Q1	32K / 77.8 GB	15	0
Qwen2.5 72B Instruct Bnb 4bit	32K / 41.4 GB	3470	8
Qwen2.5 72B Instruct 4bit	32K / 40.9 GB	1200	7

Note: green Score (e.g. "73.2") means that the model is better than erickbp/Qwen2-72B-Instruct-AWQ-GEMM.