Qwen2.5-VL-32B-Instruct-GGUF Open-Source Multimodal Model - Outstanding at Image Understanding and Text Generation

Qwen2.5 VL 32B Instruct GGUF

Developed by lmstudio-community

Qwen2.5 VL 32B Instruct is a multimodal large language model developed by Qwen, supporting vision and language tasks with powerful image understanding and text generation capabilities.

Text-to-Image EnglishOpen Source License:Apache-2.0 #Multimodal Visual Reasoning #128k Long-Text Understanding #Structured JSON Output

Downloads 3,713

Release Time : 3/27/2025

Model Overview

This model excels at recognizing common objects (such as flowers, birds, fish, insects) and efficiently analyzing text, charts, icons, graphics, and layouts within images. It can serve as a visual agent with dynamic reasoning and tool-calling capabilities, supporting both computer and mobile operations. Suitable for generating structured outputs and stable JSON-format results, it supports multiple languages.

Model Features

Multimodal Capabilities

Supports vision and language tasks, capable of processing both image and text inputs simultaneously.

Long Context Support

Supports context lengths of up to 128k tokens, suitable for handling long documents or complex tasks.

Structured Output

Capable of generating stable JSON-format results, ideal for applications requiring structured data.

Dynamic Reasoning & Tool Calling

Can function as a visual agent, supporting dynamic reasoning and tool calling for computer and mobile operations.

Model Capabilities

Text generation

Image analysis

Chart recognition

Layout analysis

Multilingual support

Structured output generation

Dynamic reasoning

Tool calling

Use Cases

Visual Assistance

Image Content Description

Analyzes image content and generates detailed textual descriptions.

Accurately identifies objects, scenes, and text within images.

Chart Parsing

Parses charts, graphs, and data within images.

Extracts key information from charts and generates structured data.

Automation Tools

Computer Operation Agent

Acts as a visual agent to perform computer operation tasks.

Completes automation tasks through image recognition and tool calling.

quantized_by: bartowski pipeline_tag: text-generation base_model: Qwen/Qwen2.5-VL-32B-Instruct license: apache-2.0 tags:

multimodal language:
en base_model_relation: quantized

üí´ Community Model> Qwen2.5 VL 32B Instruct by Qwen

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Model creator: Qwen
Original model: Qwen2.5-VL-32B-Instruct
GGUF quantization: provided by bartowski based on llama.cpp release b5284

Technical Details

Supports context length of 128k tokens.

Proficient in recognizing common objects such as flowers, birds, fish, and insects, but it is highly capable of analyzing texts, charts, icons, graphics, and layouts within images.

Capable of acting as a visual agent that can reason and dynamically direct tools, which is capable of computer use and phone use.

Useful for generating structured outputs and stable JSON outputs.

Multilingual support.

Special thanks

üôè Special thanks to Georgi Gerganov and the whole team working on llama.cpp for making all of this possible.

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