{"id":3140,"date":"2026-03-13T15:30:27","date_gmt":"2026-03-13T19:30:27","guid":{"rendered":"https:\/\/ozer.gt\/log\/?p=3140"},"modified":"2026-03-13T15:49:17","modified_gmt":"2026-03-13T19:49:17","slug":"which-llms-can-you-run-locally","status":"publish","type":"post","link":"https:\/\/ozer.gt\/log\/2026\/03\/13\/which-llms-can-you-run-locally\/","title":{"rendered":"Which LLMs can you run locally?"},"content":{"rendered":"<p><a href=\"https:\/\/www.canirun.ai\" target=\"_blank\" rel=\"noopener\">This project<\/a> helps you find out which models your machine can handle.<\/p>\n<p>If you&#8217;re a data scientist experimenting with local models, getting an idea of what you can run locally is better than wasting time setting up huge models. The auto-detection isn&#8217;t perfect, and the list is missing some hardware combinations, but the convenience still makes it useful.<\/p>\n<p>This is also useful if you&#8217;re running a workshop or demo. In my courses like AI Applications, we experiment with LLMs in Docker containers, but performance varies greatly by hardware.<\/p>\n<p>This new webtool is a nice, fast alternative for selecting models. You can also use the more accurate CLI tool <a href=\"https:\/\/github.com\/AlexsJones\/llmfit\" target=\"_blank\" rel=\"noopener\">llmfit<\/a>, but that takes an install or a Docker pull and run.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>This project helps you find out which models your machine can handle. If you&#8217;re a data scientist experimenting with local models, getting an idea of what you can run locally is better than wasting time setting up huge models. The auto-detection isn&#8217;t perfect, and the list is missing some hardware combinations, but the convenience still [&hellip;]<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"cybocfi_hide_featured_image":"","footnotes":""},"categories":[1],"tags":[],"class_list":["post-3140","post","type-post","status-publish","format-standard","hentry","category-uncategorized"],"_links":{"self":[{"href":"https:\/\/ozer.gt\/log\/wp-json\/wp\/v2\/posts\/3140","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/ozer.gt\/log\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/ozer.gt\/log\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/ozer.gt\/log\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/ozer.gt\/log\/wp-json\/wp\/v2\/comments?post=3140"}],"version-history":[{"count":31,"href":"https:\/\/ozer.gt\/log\/wp-json\/wp\/v2\/posts\/3140\/revisions"}],"predecessor-version":[{"id":3171,"href":"https:\/\/ozer.gt\/log\/wp-json\/wp\/v2\/posts\/3140\/revisions\/3171"}],"wp:attachment":[{"href":"https:\/\/ozer.gt\/log\/wp-json\/wp\/v2\/media?parent=3140"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/ozer.gt\/log\/wp-json\/wp\/v2\/categories?post=3140"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/ozer.gt\/log\/wp-json\/wp\/v2\/tags?post=3140"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}