[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"$fG8WmZu0GoqTvcQlIXJT8rDmnCxPDP8LFYC0dBMmlo8w":3},{"item":4},{"id":5,"idKnowledge":6,"idDomain":7,"idCluster":7,"kindOverride":8,"slug":9,"title":10,"description":11,"bodyMarkdown":12,"bodyHtml":13,"author":14,"date":15,"createdAt":16,"topics":17,"image":20,"hasDownload":21,"fileName":7,"youtubeId":20},"502","EABD873D-A1A9-3346-8FA5-5EDD92FAC13F","","article","what-if-your-computers-could-team-up-to-run-ai-models-too-big-for-one-machine","What If Your Computers Could Team Up to Run AI Models Too Big for One Machine?","Pooled.run lets multiple devices combine their available memory to run large AI models that would normally be too big for a single machine. Here’s how it works and why it’s interesting.","# What If Your Computers Could Team Up to Run AI Models Too Big for One Machine?\n\nWhat if you didn't need a powerful GPU with 48GB or 80GB of VRAM to run a large AI model?\n\nWhat if you could simply **combine the memory of multiple machines** and use them together?\n\nThat's the idea behind **Pooled.run**.\n\n## What is Pooled.run?\n\nPooled.run is an open-source technology that allows multiple devices to work together to run large AI models.\n\nInstead of requiring one machine to have enough memory for the entire model, the model can be distributed across multiple connected devices.\n\nFor example:\n\n- Computer A → 12GB memory\n- Computer B → 16GB memory\n- Computer C → 8GB memory\n\nTogether, they can provide around **36GB of available memory** for the workload.\n\n## How does it work?\n\nThink of a large AI model as a huge building.\n\nInstead of forcing one computer to hold the entire building, Pooled.run divides the workload between multiple computers.\n\n```text\n                Large AI Model\n                      ↓\n          ┌───────────┼───────────┐\n          ↓           ↓           ↓\n      Computer A  Computer B  Computer C\n       Part 1       Part 2       Part 3\n          └───────────┼───────────┘\n                      ↓\n                 AI Response","\u003Ch1>What If Your Computers Could Team Up to Run AI Models Too Big for One Machine?\u003C\u002Fh1>\n\u003Cp>What if you didn't need a powerful GPU with 48GB or 80GB of VRAM to run a large AI model?\u003C\u002Fp>\n\u003Cp>What if you could simply \u003Cstrong>combine the memory of multiple machines\u003C\u002Fstrong> and use them together?\u003C\u002Fp>\n\u003Cp>That's the idea behind \u003Cstrong>Pooled.run\u003C\u002Fstrong>.\u003C\u002Fp>\n\u003Ch2>What is Pooled.run?\u003C\u002Fh2>\n\u003Cp>Pooled.run is an open-source technology that allows multiple devices to work together to run large AI models.\u003C\u002Fp>\n\u003Cp>Instead of requiring one machine to have enough memory for the entire model, the model can be distributed across multiple connected devices.\u003C\u002Fp>\n\u003Cp>For example:\u003C\u002Fp>\n\u003Cul>\n\u003Cli>Computer A → 12GB memory\u003C\u002Fli>\n\u003Cli>Computer B → 16GB memory\u003C\u002Fli>\n\u003Cli>Computer C → 8GB memory\u003C\u002Fli>\n\u003C\u002Ful>\n\u003Cp>Together, they can provide around \u003Cstrong>36GB of available memory\u003C\u002Fstrong> for the workload.\u003C\u002Fp>\n\u003Ch2>How does it work?\u003C\u002Fh2>\n\u003Cp>Think of a large AI model as a huge building.\u003C\u002Fp>\n\u003Cp>Instead of forcing one computer to hold the entire building, Pooled.run divides the workload between multiple computers.\u003C\u002Fp>\n\u003Cpre>\u003Ccode class=\"language-text\">                Large AI Model\n                      ↓\n          ┌───────────┼───────────┐\n          ↓           ↓           ↓\n      Computer A  Computer B  Computer C\n       Part 1       Part 2       Part 3\n          └───────────┼───────────┘\n                      ↓\n                 AI Response\n\u003C\u002Fcode>\u003C\u002Fpre>\n","Bhushan","2026-09-28",1790578327000,[18,19],"Distributed Computing","Pooled.run",null,false]