Holo2
H Company’s Holo2 model family delivers cost-efficient, high-performance vision-language models tailored for computer-use agents that navigate, localize UI elements, and act across web, desktop, and mobile environments. The series, available in 4 B, 8 B, and 30 B-A3B sizes, builds on their earlier Holo1 and Holo1.5 models, retaining strong UI grounding while significantly enhancing navigation capabilities. Holo2 models use a mixture-of-experts (MoE) architecture, activating only necessary parameters, to optimize efficiency. Trained on curated localization and agent datasets, they can be deployed as drop-in replacements for their predecessors. They support seamless inference in frameworks compatible with Qwen3-VL models and can be integrated into agentic pipelines like Surfer 2. In benchmark testing, Holo2-30B-A3B achieved 66.1% accuracy on ScreenSpot-Pro and 76.1% on OSWorld-G, leading the UI localization category.
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Agent S2
Agent S2 is an open, modular, and scalable framework for computer-use agents developed by Simular. These autonomous AI agents interact directly with graphical user interfaces (GUIs) on desktops, mobile devices, browsers, and various software applications, mimicking human-like control via mouse and keyboard. Building upon the initial Agent S framework, Agent S2 enhances performance and modularity by integrating both frontier foundation models and specialized models. It achieves state-of-the-art results, notably surpassing previous benchmarks on OSWorld and AndroidWorld evaluations. Key design principles include proactive hierarchical planning, where the agent dynamically updates its plans after each subtask; visual grounding for precise GUI interaction using raw screenshots; an improved Agent-Computer Interface (ACI) that delegates complex tasks to specialized modules; and an agentic memory mechanism that enables continual learning from experience.
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voyage-4-large
The Voyage 4 model family from Voyage AI is a new generation of text embedding models designed to produce high-quality semantic vectors with an industry-first shared embedding space that lets different models in the series generate compatible embeddings so developers can mix and match models for document and query embedding to optimize accuracy, latency, and cost trade-offs. It includes voyage-4-large (a flagship model using a mixture-of-experts architecture delivering state-of-the-art retrieval accuracy at about 40% lower serving cost than comparable dense models), voyage-4 (balancing quality and efficiency), voyage-4-lite (high-quality embeddings with fewer parameters and lower compute cost), and the open-weight voyage-4-nano (ideal for local development and prototyping with an Apache 2.0 license). All four models in the series operate in a single shared embedding space, so embeddings generated by different variants are interchangeable, enabling asymmetric retrieval strategies.
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Surfer
You work hard gathering your data. Don’t settle for subpar visualization. Utilize Surfer’s extensive modeling tools to display your data the way it deserves while maintaining accuracy and precision. Clearly communicate information related to geology, hydrology, environmental, construction and more with Surfer. Discover the depths of your data with Surfer’s numerous analysis tools, made specifically with engineers, geologists and researchers in mind. Adjust interpolation and gridding parameters, assess the spatial continuity of data with variograms, define faults and breaklines, or perform grid calculations such as volumes, transformations, smoothing, or filtering. Surfer quickly transforms your data into knowledge.
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