{"id":3525,"date":"2026-03-08T10:58:35","date_gmt":"2026-03-08T10:58:35","guid":{"rendered":"https:\/\/paramus.ai\/app\/orca\/"},"modified":"2026-03-08T11:26:16","modified_gmt":"2026-03-08T11:26:16","slug":"orca","status":"publish","type":"page","link":"https:\/\/paramus.ai\/app\/orca\/","title":{"rendered":"ORCA"},"content":{"rendered":"\n<p style=\"font-size:14px\"><a href=\"https:\/\/paramus.ai\/app_store\/\">&larr; Back to App Store<\/a><\/p>\n\n\n\n<h1 class=\"wp-block-heading has-text-align-center\" style=\"font-size:42px;margin-bottom:0.3em\">ORCA<\/h1>\n\n\n\n<p class=\"has-text-align-center\"><span style=\"color:#666\">Computing Applications (HPC)<\/span>&nbsp;&nbsp;<span style=\"background:#198754;color:#fff;padding:3px 10px;border-radius:4px;font-size:13px\">Academic free \/ commercial license (Partial)<\/span><\/p>\n\n\n\n<h3 class=\"wp-block-heading\" style=\"margin-top:1.5em\">About<\/h3>\n\n\n\n<p>A <strong>versatile quantum chemistry program<\/strong> supporting DFT, ab initio, and semi-empirical methods. ORCA enables accurate calculations of molecular structures, spectra, and reaction mechanisms and serves as a backend for AI-assisted computational chemistry workflows.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\" style=\"margin-top:1.2em\">Key Features<\/h3>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Methods: DFT, HF, MP2, CCSD(T), CASSCF<\/li>\n\n\n\n<li>Spectroscopy: NMR, EPR, UV-Vis, IR, Raman<\/li>\n\n\n\n<li>Solvation: CPCM, SMD models<\/li>\n\n\n\n<li>Parallelization: MPI, OpenMP<\/li>\n<\/ul>\n\n\n\n<div class=\"wp-block-buttons is-content-justification-center is-layout-flex wp-container-core-buttons-is-layout-a89b3969 wp-block-buttons-is-layout-flex\">\n<div class=\"wp-block-button has-custom-width wp-block-button__width-50\"><a class=\"wp-block-button__link has-background has-medium-font-size wp-element-button\" href=\"https:\/\/www.faccts.de\/orca\/\" style=\"border-radius:4px;background-color:#000\" target=\"_blank\" rel=\"noreferrer noopener nofollow\">Buy<\/a><\/div>\n\n<div class=\"wp-block-button has-custom-width wp-block-button__width-50\"><a class=\"wp-block-button__link has-background has-medium-font-size wp-element-button\" href=\"https:\/\/orcaforum.kofo.mpg.de\/\" style=\"border-radius:4px;background-color:#000\" target=\"_blank\" rel=\"noreferrer noopener\">Activate<\/a><\/div>\n<\/div>\n\n\n\n<p class=\"has-small-font-size\">Free for academic use. Commercial license via FACCTs GmbH.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\" style=\"margin-top:1.2em\">Citation<\/h3>\n\n\n\n<p style=\"font-size:13px;line-height:1.5\"><strong>Neese, F.<\/strong> The ORCA program system. WIREs Comput. Mol. Sci. 12, e1606 (<strong>2022<\/strong>). DOI:10.1002\/wcms.1606<\/p>\n\n\n\n<h3 class=\"wp-block-heading\" style=\"margin-top:1.5em\">Frequently Asked Questions<\/h3>\n\n\n\n<h5 class=\"wp-block-heading\" style=\"margin-top:1em;margin-bottom:0.3em\">What is ORCA?<\/h5>\n\n\n\n<p style=\"font-size:14px;line-height:1.6\">ORCA is a computing applications (hpc) application available in the Paramus App Store. A versatile quantum chemistry program supporting DFT, ab initio, and semi-empirical methods. ORCA enables accurate calculations of molecular structures, spectra, and reaction mechanisms and serves as a backend for AI-assisted computational chemistry workflows.<\/p>\n\n\n\n<h5 class=\"wp-block-heading\" style=\"margin-top:1em;margin-bottom:0.3em\">Is ORCA free to use?<\/h5>\n\n\n\n<p style=\"font-size:14px;line-height:1.6\">Yes. ORCA is distributed under the Academic free \/ commercial license (Partial) license and is available at no cost through the Paramus App Store.<\/p>\n\n\n\n<h5 class=\"wp-block-heading\" style=\"margin-top:1em;margin-bottom:0.3em\">How do I install ORCA?<\/h5>\n\n\n\n<p style=\"font-size:14px;line-height:1.6\">ORCA is installed through Paramus Chemistry OS, an on-premise Windows platform for computational chemistry. Open the Paramus App Store in your local installation and select ORCA for one-click deployment.<\/p>\n\n\n\n<h5 class=\"wp-block-heading\" style=\"margin-top:1em;margin-bottom:0.3em\">What are the key features of ORCA?<\/h5>\n\n\n\n<p style=\"font-size:14px;line-height:1.6\">Key features of ORCA include: Methods: DFT, HF, MP2, CCSD(T), CASSCF; Spectroscopy: NMR, EPR, UV-Vis, IR, Raman; Solvation: CPCM, SMD models; Parallelization: MPI, OpenMP.<\/p>\n\n\n\n<h5 class=\"wp-block-heading\" style=\"margin-top:1em;margin-bottom:0.3em\">What type of application is ORCA?<\/h5>\n\n\n\n<p style=\"font-size:14px;line-height:1.6\">ORCA belongs to the &#8220;Computing Applications (HPC)&#8221; category in the Paramus App Store. It runs on Paramus Chemistry OS and can also be accessed through Paramus Cloud for supported workflows.<\/p>\n\n\n\n<h5 class=\"wp-block-heading\" style=\"margin-top:1em;margin-bottom:0.3em\">What platform does ORCA run on?<\/h5>\n\n\n\n<p style=\"font-size:14px;line-height:1.6\">ORCA runs on Paramus Chemistry OS, a Windows-based on-premise platform that provides local compute power for demanding simulations. It requires a Paramus OS installation with appropriate hardware resources.<\/p>\n\n\n\n<h5 class=\"wp-block-heading\" style=\"margin-top:1em;margin-bottom:0.3em\">Can ORCA be automated or integrated with AI workflows?<\/h5>\n\n\n\n<p style=\"font-size:14px;line-height:1.6\">Yes. ORCA is available as part of the Paramus ecosystem which supports MCP (Model Context Protocol) tools for AI-driven automation. This enables integration with large language models and automated research pipelines.<\/p>\n\n\n\n<h5 class=\"wp-block-heading\" style=\"margin-top:1em;margin-bottom:0.3em\">How should I cite ORCA in publications?<\/h5>\n\n\n\n<p style=\"font-size:14px;line-height:1.6\">The recommended citation for ORCA is: Neese, F. The ORCA program system. WIREs Comput. Mol. Sci. 12, e1606 (2022). DOI:10.1002\/wcms.1606<\/p>\n\n\n\n<script type=\"application\/ld+json\">{\"@context\":\"https:\/\/schema.org\",\"@type\":\"FAQPage\",\"mainEntity\":[{\"@type\":\"Question\",\"name\":\"What is ORCA?\",\"acceptedAnswer\":{\"@type\":\"Answer\",\"text\":\"ORCA is a computing applications (hpc) application available in the Paramus App Store. A versatile quantum chemistry program supporting DFT, ab initio, and semi-empirical methods. 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DOI:10.1002\/wcms.1606\"}}]}<\/script>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity is-style-wide\"\/>\n\n\n\n<p class=\"has-text-align-center\" style=\"font-size:14px\"><a href=\"https:\/\/paramus.ai\/app_store\/\">Browse all apps in the Paramus App Store<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"<p>&larr; Back to App Store ORCA Computing Applications (HPC)&nbsp;&nbsp;Academic free \/ commercial license (Partial) About A versatile quantum chemistry program [&hellip;]<\/p>\n","protected":false},"author":1,"featured_media":0,"parent":3511,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"content-type":"","inline_featured_image":false,"site-sidebar-layout":"default","site-content-layout":"","ast-site-content-layout":"default","site-content-style":"default","site-sidebar-style":"default","ast-global-header-display":"","ast-banner-title-visibility":"","ast-main-header-display":"","ast-hfb-above-header-display":"","ast-hfb-below-header-display":"","ast-hfb-mobile-header-display":"","site-post-title":"","ast-breadcrumbs-content":"","ast-featured-img":"","footer-sml-layout":"","ast-disable-related-posts":"","theme-transparent-header-meta":"","adv-header-id-meta":"","stick-header-meta":"","header-above-stick-meta":"","header-main-stick-meta":"","header-below-stick-meta":"","astra-migrate-meta-layouts":"default","ast-page-background-enabled":"default","ast-page-background-meta":{"desktop":{"background-color":"var(--ast-global-color-5)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""},"tablet":{"background-color":"","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""},"mobile":{"background-color":"","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""}},"ast-content-background-meta":{"desktop":{"background-color":"var(--ast-global-color-4)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""},"tablet":{"background-color":"var(--ast-global-color-4)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""},"mobile":{"background-color":"var(--ast-global-color-4)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""}},"footnotes":""},"wf_page_folders":[24],"class_list":["post-3525","page","type-page","status-publish","hentry"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v27.5 - https:\/\/yoast.com\/product\/yoast-seo-wordpress\/ -->\n<title>ORCA - Chemistry for AI<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/paramus.ai\/app\/orca\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"ORCA - Chemistry for AI\" \/>\n<meta property=\"og:description\" content=\"&larr; 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