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Average Ratings 0 Ratings
Description
GLM-4.1V is an advanced vision-language model that offers a robust and streamlined multimodal capability for reasoning and understanding across various forms of media, including images, text, and documents. The 9-billion-parameter version, known as GLM-4.1V-9B-Thinking, is developed on the foundation of GLM-4-9B and has been improved through a unique training approach that employs Reinforcement Learning with Curriculum Sampling (RLCS). This model accommodates a context window of 64k tokens and can process high-resolution inputs, supporting images up to 4K resolution with any aspect ratio, which allows it to tackle intricate tasks such as optical character recognition, image captioning, chart and document parsing, video analysis, scene comprehension, and GUI-agent workflows, including the interpretation of screenshots and recognition of UI elements. In benchmark tests conducted at the 10 B-parameter scale, GLM-4.1V-9B-Thinking demonstrated exceptional capabilities, achieving the highest performance on 23 out of 28 evaluated tasks. Its advancements signify a substantial leap forward in the integration of visual and textual data, setting a new standard for multimodal models in various applications.
Description
OmniParser serves as an advanced technique for converting user interface screenshots into structured components, which notably improves the accuracy of multimodal models like GPT-4 in executing actions that are properly aligned with specific areas of the interface. This method excels in detecting interactive icons within user interfaces and comprehending the meanings of different elements present in a screenshot, thereby linking intended actions to the appropriate screen locations. To facilitate this process, OmniParser assembles a dataset for interactable icon detection that includes 67,000 distinct screenshot images, each annotated with bounding boxes around interactable icons sourced from DOM trees. Furthermore, it utilizes a set of 7,000 pairs of icons and their descriptions to refine a captioning model tasked with extracting the functional semantics of the identified elements. Comparative assessments on various benchmarks, including SeeClick, Mind2Web, and AITW, reveal that OmniParser surpasses the performance of GPT-4V baselines, demonstrating its effectiveness even when relying solely on screenshot inputs without supplementary context. This advancement not only enhances the interaction capabilities of AI models but also paves the way for more intuitive user experiences across digital interfaces.
API Access
Has API
API Access
Has API
Integrations
Claude Code
Cline
Cua
GPT-4
Kilo Code
OpenRouter
Roo Code
Sup AI
Integrations
Claude Code
Cline
Cua
GPT-4
Kilo Code
OpenRouter
Roo Code
Sup AI
Pricing Details
Free
Free Trial
Free Version
Pricing Details
No price information available.
Free Trial
Free Version
Deployment
Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook
Deployment
Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook
Customer Support
Business Hours
Live Rep (24/7)
Online Support
Customer Support
Business Hours
Live Rep (24/7)
Online Support
Types of Training
Training Docs
Webinars
Live Training (Online)
In Person
Types of Training
Training Docs
Webinars
Live Training (Online)
In Person
Vendor Details
Company Name
Zhipu AI
Founded
2023
Country
China
Website
chat.z.ai/
Vendor Details
Company Name
Microsoft
Founded
1975
Country
United States
Website
microsoft.github.io/OmniParser/