HomeMininglamp Launches Cider+Mano-P, Transforming Mac into a Private AI Workstation
Recently, Mininglamp open-sourced two key local AI projects—Cider and Mano-P—that solve critical challenges in Mac inference acceleration and GUI agent operations, offering users a full local AI setup. This transforms the Mac from merely being "able to run AI" into an efficient, private, and deeply controllable AI workstation.
Cider: Unlocking M-Series Chip Potential for Faster, More Efficient Local LLM/VLM Execution
When running local large models on a Mac, many users find that despite powerful hardware, inference speed and memory use often fall short. Cider was built to address this exact problem.
This project fully taps into the INT8 TensorOps engine of M-series chips (particularly the M5), dramatically boosting local inference performance for LLMs and VLMs while slashing memory usage. It offers Mac users a tangible way to run AI models efficiently on edge devices.
Mano-P: A Pure Visual GUI Agent That Enables Full AI "Screen Viewing and Operation" Workflow
While Cider focuses on speed, Mano-P tackles usability—giving AI the ability to understand and control computers just like a human.
Mano-P is a GUI-VLA agent designed for edge devices, running locally on Mac mini and MacBook. It goes beyond browser-only agents, enabling direct interaction with desktop applications, web interfaces, professional tools, and intricate graphical workflows.
Its core capabilities include:
Complex GUI automation operations, cross-system data integration, long-task planning and execution, intelligent report generation, self-built application developmentThe system relies on pure visual GUI operations, so screenshots and task data never leave the device, ensuring complete privacy and security.
Practical Demonstration: Mano-P Learns Mahjong and Makes Autonomous Decisions
In the demo, Mano-P demonstrated strong performance in a mahjong game. Using only visual perception, it recognizes cards, analyzes the situation, and makes decisions—showing a complete "perception to action" loop.
Two Open Source Projects Join Forces to Create a Private Local AI Infrastructure
Cider (edge inference acceleration) and Mano-P (edge GUI agent) together make a complete local AI stack. Whether you want top inference speed or AI that can handle complex desktop tasks on its own, you get a more capable and private AI experience on Mac.
AIbase Comment: With the growing need for local model deployment, Mininglamp's open-sourcing of Cider and Mano-P directly addresses Mac users' pain points, offering a key reference for practical edge AI and ecosystem growth. Developers interested can check the latest updates and build their own local AI workstation.
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![KeithMoore]()
Just got my M3 Max and was waiting for something like this to make it a true AI powerhouse. Local inference is the future, especially with privacy concerns skyrocketing. Thanks for open-sourcing Cider and Mano-P—can't wait to tinker with GUI agents on my machine! 🖥️✨
Recently, Mininglamp open-sourced two key local AI projects—Cider and Mano-P—that solve critical challenges in Mac inference acceleration and GUI agent operations, offering users a full local AI setup. This transforms the Mac from merely being "able to run AI" into an efficient, private, and deeply controllable AI workstation.
Cider: Unlocking M-Series Chip Potential for Faster, More Efficient Local LLM/VLM Execution
When running local large models on a Mac, many users find that despite powerful hardware, inference speed and memory use often fall short. Cider was built to address this exact problem.
This project fully taps into the INT8 TensorOps engine of M-series chips (particularly the M5), dramatically boosting local inference performance for LLMs and VLMs while slashing memory usage. It offers Mac users a tangible way to run AI models efficiently on edge devices.
Mano-P: A Pure Visual GUI Agent That Enables Full AI "Screen Viewing and Operation" Workflow
While Cider focuses on speed, Mano-P tackles usability—giving AI the ability to understand and control computers just like a human.
Mano-P is a GUI-VLA agent designed for edge devices, running locally on Mac mini and MacBook. It goes beyond browser-only agents, enabling direct interaction with desktop applications, web interfaces, professional tools, and intricate graphical workflows.
Its core capabilities include:
Complex GUI automation operations, cross-system data integration, long-task planning and execution, intelligent report generation, self-built application developmentThe system relies on pure visual GUI operations, so screenshots and task data never leave the device, ensuring complete privacy and security.
Practical Demonstration: Mano-P Learns Mahjong and Makes Autonomous Decisions
In the demo, Mano-P demonstrated strong performance in a mahjong game. Using only visual perception, it recognizes cards, analyzes the situation, and makes decisions—showing a complete "perception to action" loop.
Two Open Source Projects Join Forces to Create a Private Local AI Infrastructure
Cider (edge inference acceleration) and Mano-P (edge GUI agent) together make a complete local AI stack. Whether you want top inference speed or AI that can handle complex desktop tasks on its own, you get a more capable and private AI experience on Mac.
AIbase Comment: With the growing need for local model deployment, Mininglamp's open-sourcing of Cider and Mano-P directly addresses Mac users' pain points, offering a key reference for practical edge AI and ecosystem growth. Developers interested can check the latest updates and build their own local AI workstation.
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Just got my M3 Max and was waiting for something like this to make it a true AI powerhouse. Local inference is the future, especially with privacy concerns skyrocketing. Thanks for open-sourcing Cider and Mano-P—can't wait to tinker with GUI agents on my machine! 🖥️✨
