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Mano-P Alternatives
Similar projects and alternatives to Mano-P
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cider
W8A8/W4A8 inference on Apple Silicon — unlocking unused INT8 TensorOps in M5 for 1.2–1.9× faster LLM prefill, built as MLX custom primitives. (by Mininglamp-AI)
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SaaSHub
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gnome-workflows
Discontinued Allow users to build complex workflows that are launched like any application.
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OSWorld
[NeurIPS 2024] OSWorld: Benchmarking Multimodal Agents for Open-Ended Tasks in Real Computer Environments
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computeruseprotocol
Discontinued Computer Use Protocol is a universal schema for AI agents to perceive and interact with any desktop UI.
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UI-Ins
Official implementation of UI-Ins: Enhancing GUI Grounding with Multi-Perspective Instruction-as-Reasoning
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nexa-sdk
Run frontier LLMs and VLMs with day-0 model support across GPU, NPU, and CPU, with comprehensive runtime coverage for PC (Python/C++), mobile (Android & iOS), and Linux/IoT (Arm64 & x86 Docker). Supporting OpenAI GPT-OSS, IBM Granite-4, Qwen-3-VL, Gemma-3n, Ministral-3, and more.
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mano-afk
Full-stack app builder that goes from user natural language to a deployed, tested, and bug-fixed application — fully autonomously. Multi-agent architecture with GUI testing (mano-cua) and adversary code review. Evolves with each project.
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kwin-mcp
MCP server for Linux desktop GUI automation on KDE Plasma 6 Wayland -- 30 tools for virtual and live sessions
NOTE:
The number of mentions on this list indicates mentions on common posts plus user suggested alternatives.
Hence, a higher number means a better Mano-P alternative or higher similarity.
Mano-P discussion
Mano-P reviews and mentions
Posts with mentions or reviews of Mano-P.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2026-06-11.
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Will AI Agents Replace Programmers?
Learn more on GitHub: https://github.com/Mininglamp-AI/Mano-P
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What Is RAG? Why LLM Memory Alone Is Never Enough
Our team has been working on edge AI for a while. Mano-P is an open-source GUI agent model built for Apple Silicon devices. Its 4B quantized version runs locally on a Mac mini (M4 chip, 32GB RAM) at ~80 tokens/s decode speed, and the companion Cider SDK adds INT8 activation quantization that delivers 1.4x–2.2x prefill speedup. Mano-P currently ranks #1 on OSWorld among specialized GUI agent models with a 58.2% success rate, with all inference executed entirely on-device — screenshots and task data never leave the machine.
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SFT Offline RL Online RL: The Three-Stage Training Pipeline Behind Mano-P
Mano-P is Apache 2.0 licensed. The code is at github.com/Mininglamp-AI/Mano-P, and the technical paper is on arXiv:2509.17336. If you're working on agent training pipelines — especially for grounded, interactive domains — we'd be interested to hear what works and what doesn't.
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NVIDIA and Apple Solved the Hardware. Here's What's Left to Build.
Mano-P takes this path. It's an Apache 2.0 licensed GUI-VLA (Vision-Language-Action) agent designed specifically for edge devices, focused on GUI automation.
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Your AI Vendor Says 'Trust Us' with Your Data. There's a Better Option.
The open-source community is already shipping this model. Mano-P is an Apache 2.0 licensed GUI agent project built for edge devices. It runs inference entirely on-device on Macs with Apple M4 chip and 32GB RAM. In local mode, all screenshots and task descriptions are processed on-device with zero network transmission. The full source code is public and the data flow path is auditable.
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NVIDIA Showed an Agent Building Architecture on a Laptop — No Cloud Required
Before diving into the architecture, it's worth noting that the open-source community is already shipping working implementations. Mano-P is an Apache 2.0 licensed GUI Agent model designed specifically for edge devices. It runs complex GUI automation tasks entirely on-device on Apple Silicon Macs — no cloud calls, no data leaving the machine. I'll reference its benchmark data throughout this post as ground truth for where on-device AI actually stands today.
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NVIDIA Put Petaflop Compute on Your Desk — And It Changes the AI Cost Equation
For a concrete data point: the open-source project Mano-P offers a 72B model that scored 58.2% on the OSWorld benchmark, ranking first among specialized models (the second-place opencua-72b scored 45.0%). But the 72B variant exists primarily for benchmark evaluation. The model designed for actual edge deployment is a 4B version that decodes at 80.1 tok/s on Apple Silicon with W8A16 quantization — fast enough for real-time, interactive use.
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Your Next PC Is Not a Productivity Tool - It Is a Runtime for AI Agents
Mininglamp's open-source Mano-P is a GUI agent that runs this entire stack. It's purely vision-driven, runs locally on Mac, requires no cloud API calls, and keeps all screenshots and operation data on-device. On Apple M5 Pro it achieves roughly 80 tokens/s decode speed, which is smooth enough for daily GUI automation tasks.
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Agent Engineering Is No Longer a Research Role. Here's What Changed.
Repository: https://github.com/Mininglamp-AI/Mano-P
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Harness Tells Your Agent What to Do. GUI Agents Let It Actually Do It.
Mano-P is Apache 2.0 licensed and available on GitHub: https://github.com/Mininglamp-AI/Mano-P
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A note from our sponsor - SaaSHub
www.saashub.com | 13 Jun 2026
Stats
Basic Mano-P repo stats
19
2,318
7.2
12 days ago
Mininglamp-AI/Mano-P is an open source project licensed under Apache License 2.0 which is an OSI approved license.
The primary programming language of Mano-P is HTML.
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