What are the hardware requirements for Qwen2.5 VL 7B Instruct AWQ?

Qwen2.5 VL 7B Instruct AWQ requires approximately 6.9 GB of VRAM and supports a context window of 125K tokens. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Qwen2.5 VL 7B Instruct AWQ and how large is it?

Qwen2.5 VL 7B Instruct AWQ is developed by Qwen, a model with 7b 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 Qwen2.5 VL 7B Instruct AWQ?

Qwen2.5 VL 7B Instruct AWQ is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Qwen2.5 VL 7B Instruct AWQ by Qwen — VRAM 6.9GB, 125K context

Name: Qwen2.5 VL 7B Instruct AWQ
Author: Qwen

Qwen2.5 VL 7B Instruct AWQ is an open-source language model by Qwen. Features: 7b LLM, VRAM: 6.9GB, Context: 125K, License: apache-2.0, Quantized, Instruction-Based, LLM Explorer Score: 0.28.

Arxiv:2308.12966 Arxiv:2309.00071 Arxiv:2409.12191 4-bit Awq Base model:quantized:qwen/qwen... Base model:qwen/qwen2.5-vl-7b-... Conversational En Endpoints compatible Image-text-to-text Instruct Multimodal Quantized Qwen2 5 vl Region:us Safetensors Sharded Tensorflow

Model Card on HF 🤗: https://huggingface.co/Qwen/Qwen2.5-VL-7B-Instruct-AWQ

Qwen2.5 VL 7B Instruct AWQ Parameters and Internals

LLM Name	Qwen2.5 VL 7B Instruct AWQ
Repository 🤗	https://huggingface.co/Qwen/Qwen2.5-VL-7B-Instruct-AWQ
Base Model(s)	Qwen/Qwen2.5-VL-7B-Instruct Qwen/Qwen2.5-VL-7B-Instruct
Model Size	7b
Required VRAM	6.9 GB
Updated	2026-08-09
Maintainer	Qwen
Model Type	qwen2_5_vl
Instruction-Based	Yes
Model Files	4.0 GB: 1-of-2 2.9 GB: 2-of-2
Supported Languages	en
AWQ Quantization	Yes
Quantization Type	awq
Model Architecture	Qwen2_5_VLForConditionalGeneration
License	apache-2.0
Context Length	128000
Model Max Length	128000
Transformers Version	4.49.0.dev0
Tokenizer Class	Qwen2Tokenizer
Padding Token	<\|endoftext\|>
Vocabulary Size	152064
Torch Data Type	bfloat16
Errors	replace

Rank the Qwen2.5 VL 7B Instruct AWQ 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 Qwen2.5 VL 7B Instruct AWQ

Best Alternatives	Context / RAM	Downloads	Likes
OlmOCR 2 7B 1025 Mlx 8bit	125K / 9.4 GB	172	2
OlmOCR 2 7B 1025 Mlx 4bit	125K / 5.6 GB	126	1
OlmOCR 7B 0725 8bit	125K / 9.4 GB	97	5
Qwen2.5 VL 7B Instruct 4bit	125K / 5.6 GB	3486	4
Qwen2.5 VL 7B Instruct 8bit	125K / 8.9 GB	1759	17
Jedi 7B 1080p 4bit	125K / 4.9 GB	19	1
Jedi 7B 1080p 6bit	125K / 6.9 GB	19	1
Qwen2.5 VL 7B Instruct 6bit	125K / 6.9 GB	107	3
Qwen2.5 VL 7B Instruct 3bit	125K / 4.7 GB	56	1
OmniLong Qwen2.5 VL 7B	512K / 16.6 GB	7	2