{"id":11224,"date":"2026-08-19T21:16:38","date_gmt":"2026-08-19T13:16:38","guid":{"rendered":"https:\/\/infernews.com\/blog\/14mb-foundation-model-for-tiny-devices-phones-wearables-smart-home-and-robots\/"},"modified":"2026-08-19T21:18:02","modified_gmt":"2026-08-19T13:18:02","slug":"14mb-foundation-model-for-tiny-devices-phones-wearables-smart-home-and-robots","status":"publish","type":"post","link":"https:\/\/infernews.com\/blog\/14mb-foundation-model-for-tiny-devices-phones-wearables-smart-home-and-robots\/","title":{"rendered":"needle\uff1a14MB \u672c\u5730\u5de5\u5177\u6a21\u578b\uff0c\u5c08\u653b\u7d50\u69cb\u5316\u64cd\u4f5c"},"content":{"rendered":"\n<figure class=\"wp-block-image size-large\"><img decoding=\"async\" src=\"https:\/\/infernews.com\/blog\/wp-content\/uploads\/2026\/08\/banner-1.jpg\" alt=\"Needle\"\/><\/figure>\n\n\n\n<p class=\"wp-block-paragraph\">Needle 2 \u5c6c\u65bc\u7528\u65bc tool calling \u7684\u5c0f\u578b\u6a21\u578b\uff0c\u540c\u6642\u8655\u7406 device use \u548c structured extraction\u3002\u5b83\u628a\u8f38\u5165\u6587\u5b57\u8f49\u6210\u53ef\u76f4\u63a5\u63a5\u5165\u5de5\u4f5c\u6d41\u7684\u7d50\u69cb\u5316\u7d50\u679c\uff0c\u9069\u5408\u5728\u672c\u5730\u88dd\u7f6e\u3001\u9694\u96e2\u7db2\u7d61\u74b0\u5883\u6216\u8cc7\u6e90\u5f88\u7dca\u7684\u60c5\u6cc1\u4e0b\u90e8\u7f72\u3002<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">\u9019\u500b Python package \u63d0\u4f9b inference\u3001LoRA fine-tuning \u548c export\uff0c\u5b89\u88dd\u5f8c\u6703\u5148\u5f9e Hugging Face \u4e0b\u8f09\u4e00\u6b21 engine\uff0c\u518d\u5728\u672c\u6a5f\u5feb\u53d6\uff0c\u4e4b\u5f8c\u4e0d\u518d\u4f9d\u8cf4\u7db2\u7d61\u3002\u958b\u767c\u8005\u53ea\u8981\u63cf\u8ff0\u5de5\u5177\uff0c\u6a21\u578b\u5c31\u6703\u6309 schema \u7522\u751f JSON\uff0c\u4e26\u7528 byte-level grammar \u6536\u7a84\u8f38\u51fa\u7bc4\u570d\uff0c\u6e1b\u5c11\u683c\u5f0f\u8dd1\u504f\u3002<\/p>\n\n\n<figure class=\"wp-block-embed-youtube wp-block-embed is-type-video is-provider-youtube wp-embed-aspect-16-9 wp-has-aspect-ratio\"><div class=\"lyte-wrapper\" title=\"This 14MB AI Model Runs Locally &mdash; Needle 2 Explained\" style=\"width:853px;max-width:100%;margin:5px auto;\"><div class=\"lyMe\" id=\"WYL_65zfYPCVgtk\" itemprop=\"video\" itemscope itemtype=\"https:\/\/schema.org\/VideoObject\"><div><meta itemprop=\"thumbnailUrl\" content=\"https:\/\/infernews.com\/blog\/wp-content\/plugins\/wp-youtube-lyte\/lyteCache.php?origThumbUrl=https%3A%2F%2Fi.ytimg.com%2Fvi%2F65zfYPCVgtk%2Fhqdefault.jpg\" \/><meta itemprop=\"embedURL\" content=\"https:\/\/www.youtube.com\/embed\/65zfYPCVgtk\" \/><meta itemprop=\"duration\" content=\"PT6M46S\" \/><meta itemprop=\"uploadDate\" content=\"2026-08-18T20:06:22Z\" \/><\/div><div id=\"lyte_65zfYPCVgtk\" data-src=\"https:\/\/infernews.com\/blog\/wp-content\/plugins\/wp-youtube-lyte\/lyteCache.php?origThumbUrl=https%3A%2F%2Fi.ytimg.com%2Fvi%2F65zfYPCVgtk%2Fhqdefault.jpg\" class=\"pL\"><div class=\"tC\"><div class=\"tT\" itemprop=\"name\">This 14MB AI Model Runs Locally \u2014 Needle 2 Explained<\/div><\/div><button tabindex=\"0\" class=\"play\"><\/button><div class=\"ctrl\"><div class=\"Lctrl\"><\/div><div class=\"Rctrl\"><\/div><\/div><\/div><noscript><a href=\"https:\/\/youtu.be\/65zfYPCVgtk\" rel=\"nofollow\"><img loading=\"lazy\" decoding=\"async\" src=\"https:\/\/infernews.com\/blog\/wp-content\/plugins\/wp-youtube-lyte\/lyteCache.php?origThumbUrl=https%3A%2F%2Fi.ytimg.com%2Fvi%2F65zfYPCVgtk%2F0.jpg\" alt=\"This 14MB AI Model Runs Locally &mdash; Needle 2 Explained\" width=\"853\" height=\"460\" \/><br \/>Watch this video on YouTube<\/a><\/noscript><meta itemprop=\"description\" content=\"Needle 2 is a tiny 45-million-parameter AI model from Cactus Compute designed specifically for tool calling, device control, and structured actions. The entire model is around 14MB, yet Cactus reports that it can run at hundreds of tokens per second even on hardware like a Raspberry Pi 5. In this video, we break down how Needle 2 manages to stay so small, including: Why it focuses on tool calling instead of general chat Tool retrieval Grammar-constrained decoding Hadamard MLPs Engram memory ~2.2-bit effective weight quantization Why 98% function-selection accuracy does not mean 98% complete tool-call accuracy Where tiny specialized models like this could actually be useful Needle 2 isn&#039;t trying to replace frontier models. Instead, it shows that many simple AI tasks might not need billions of parameters in the first place. #LLM #Needle2 #LocalAI #MachineLearning #AI\"><\/div><\/div><div class=\"lL\" style=\"max-width:100%;width:853px;margin:5px auto;\"><\/div><figcaption><\/figcaption><\/figure>\n\n\n<p class=\"wp-block-paragraph\">\u5b83\u548c\u540c\u985e\u5c0f\u6a21\u578b\u7684\u53d6\u6368\u5f88\u660e\u78ba\uff1a45M \u53c3\u6578\u3001\u55ae\u4e00 14MB binary\uff0c\u63db\u4f86\u7684\u662f\u6975\u4f4e\u8a18\u61b6\u9ad4\u4f54\u7528\u548c\u96e2\u7dda\u904b\u884c\u80fd\u529b\uff1b\u5b98\u65b9\u6e2c\u8a66\u4e5f\u986f\u793a\uff0c\u5b83\u6703\u548c FunctionGemma 270M\u3001LFM2.5 230M \u53ca Apple FM \u4e92\u6709\u52dd\u8ca0\uff0c\u4f46\u9ad4\u7a4d\u5c0f\u5f97\u591a\u3002\u53e6\u4e00\u500b\u505a\u6cd5\u662f\u52a0\u5165 confidence score\uff0c\u4f4e\u65bc\u9580\u6abb\u5c31\u53ef\u4ee5\u4ea4\u56de\u4eba\u5de5\u6216\u4e0a\u5c64\u6d41\u7a0b\u8655\u7406\u3002<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>\u55ae\u4e00\u5f15\u64ce\u6253\u5305\uff0c\u90e8\u7f72\u6642\u4e0d\u7528\u5206\u958b\u7ba1\u7406\u6b0a\u91cd\u6a94<\/li>\n\n\n\n<li>\u4ee5 JSON \u8207 schema \u7d04\u675f\u8f38\u51fa\uff0c\u65b9\u4fbf\u4e32\u63a5\u5de5\u5177\u93c8<\/li>\n\n\n\n<li>\u652f\u63f4\u5927\u91cf\u5de5\u5177\u76ee\u9304\uff0c\u4f46\u6bcf\u8f2a\u53ea\u53d6 top five<\/li>\n\n\n\n<li>256-token sliding window \u4ee4\u8a18\u61b6\u9ad4\u7dad\u6301\u5728\u7d04 28MB<\/li>\n\n\n\n<li>\u9069\u5408\u96e2\u7dda\u88dd\u7f6e\u3001\u908a\u7de3\u8a2d\u5099\u548c\u9700\u8981\u7a69\u5b9a\u7d50\u69cb\u8f38\u51fa\u7684\u5718\u968a<\/li>\n<\/ul>\n\n\n\n<p class=\"wp-block-paragraph\"><a href=\"https:\/\/github.com\/cactus-compute\/needle\" rel=\"noopener noreferrer\"><strong>GitHub<\/strong><\/a>\u00a0\u00b7\u00a0<strong><a href=\"https:\/\/huggingface.co\/Cactus-Compute\/needle2\">\u6a21\u578b<\/a><\/strong><\/p>\n","protected":false},"excerpt":{"rendered":"<p>Needle 2 \u628a\u5de5\u5177\u547c\u53eb\u3001\u88dd\u7f6e\u64cd\u4f5c\u548c\u7d50\u69cb\u5316\u62bd\u53d6\u6536\u9032\u55ae\u4e00 14MB \u5f15\u64ce\uff0c\u672c\u5730\u8dd1\u5b8c\u6574\u5c0d\u8a71\u53ea\u9700\u7d04 28MB RAM\u3002\u5b83\u9069\u5408\u8981\u4f4e\u8a18\u61b6\u9ad4\u3001\u96e2\u7dda\u90e8\u7f72\u53c8\u8981\u8f38\u51fa JSON \u7684\u5de5\u4f5c\u6d41\u3002<\/p>\n","protected":false},"author":8,"featured_media":11223,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"ai_generated_summary":"","footnotes":""},"categories":[133,152,150,76,127,187],"tags":[],"class_list":["post-11224","post","type-post","status-publish","format-standard","hentry","category-133","category-python","category-150","category-76","category-127","category-187"],"_links":{"self":[{"href":"https:\/\/infernews.com\/blog\/wp-json\/wp\/v2\/posts\/11224","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/infernews.com\/blog\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/infernews.com\/blog\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/infernews.com\/blog\/wp-json\/wp\/v2\/users\/8"}],"replies":[{"embeddable":true,"href":"https:\/\/infernews.com\/blog\/wp-json\/wp\/v2\/comments?post=11224"}],"version-history":[{"count":2,"href":"https:\/\/infernews.com\/blog\/wp-json\/wp\/v2\/posts\/11224\/revisions"}],"predecessor-version":[{"id":11227,"href":"https:\/\/infernews.com\/blog\/wp-json\/wp\/v2\/posts\/11224\/revisions\/11227"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/infernews.com\/blog\/wp-json\/wp\/v2\/media\/11223"}],"wp:attachment":[{"href":"https:\/\/infernews.com\/blog\/wp-json\/wp\/v2\/media?parent=11224"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/infernews.com\/blog\/wp-json\/wp\/v2\/categories?post=11224"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/infernews.com\/blog\/wp-json\/wp\/v2\/tags?post=11224"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}