Doubao Large Model 1.6-vision - A visual depth thinking model launched by Volcano Engine

What is Doubao Large Model 1.6-Vision?

Doubao Big Model 1.6-vision is a visual deep thinking model launched by Volcano Engine, featuring tool-invoking capabilities. The model boasts powerful general multimodal understanding and reasoning abilities, supports the Responses API, and can autonomously invoke tools such as positioning, cropping, point selection, line drawing, scaling, and rotation to achieve fine-grained image processing. Doubao Big Model 1.6-vision meets high-order requirements in visual understanding accuracy and reduces costs by approximately 50% compared to its predecessor, Doubao-1.5-thinking-vision-pro, offering higher cost-effectiveness. The model performs excellently in professional visual understanding public evaluations, covering multiple application scenarios such as OCR information extraction, image review, inspection and security, video and image annotation, educational problem solving, and AI search and question answering, helping enterprises build AI applications efficiently and cost-effectively.

The main functions of the Doubao large model 1.6-vision

• Tool calling capabilityDoubao Large Model 1.6-vision can automatically call tools such as POINT (drawing points and lines), GROUNDING (selecting areas), ZOOM (scaling the image), and ROTATE (rotating the image) to achieve fine processing of images.
• Multimodal understanding and reasoningThe model possesses powerful general multimodal understanding and reasoning capabilities, simulating the human visual reasoning process, from global scanning to local focusing, enhancing the interpretability of reasoning.
• Support Responses APIBy supporting the Responses API, Doubao's large model 1.6-vision can more efficiently meet customers' high-level needs for visual understanding accuracy.
• Cost-effectivenessCompared to its predecessor, the Doubao large model 1.6-vision has a total cost reduction of approximately 50%, offering higher cost-effectiveness.
• Application development efficiencyBy reducing the amount of code in the agent development process, development efficiency is improved, making application development more efficient.

Technical principles of the large-scale bean bun model 1.6-vision

• Multimodal thinking abilityDoubao Big Model 1.6-vision enables models to understand and deal with complex real-world problems more deeply through multimodal thinking capabilities.
• Differentiated capabilities of tool callsThe model can integrate images into its thought process, enabling precise processing of images such as positioning, cropping, point selection, drawing lines, scaling, and rotation.
• Simulate human visual reasoningBy simulating the human visual reasoning process of "from global scanning to local focusing", it enhances the interpretability of reasoning and completes image operations efficiently and accurately.
• Support Responses APIThe ability to independently select and invoke tools reduces the amount of code required during agent development and improves development efficiency.
• High cost performanceOverall costs are reduced by about 50%, unlocking stronger performance at a lower cost, significantly improving cost-effectiveness.

How to use the Doubao large model 1.6-vision

• Project official website: Large Bean Bun Model

Application scenarios of the Doubao large model 1.6-vision

• OCR Information ExtractionUsed to automatically identify and extract text information from images.
• Image reviewIt helps businesses automate the review of image content to ensure compliance with specific standards or policies.
• Inspection and SecurityIn security monitoring systems, it is used to identify abnormal behaviors or events and improve security efficiency.
• Video and image annotationIn video and image content analysis, tags or annotations are automatically added to facilitate retrieval and categorization.
• Educational Problem Solving: To assist the education industry by using image recognition and understanding to answer academic questions or provide teaching support.
• AI Search Q&AImage recognition technology can be used in search engines to improve the relevance and accuracy of search results.