{"id":214683,"date":"2026-02-11T19:12:00","date_gmt":"2026-02-12T00:12:00","guid":{"rendered":"https:\/\/news-you-need.com\/index.php\/2026\/02\/11\/z-ais-open-source-glm-5-achieves-record-low-hallucination-rate-and-leverages-new-rl-slime-technique\/"},"modified":"2026-02-17T20:15:26","modified_gmt":"2026-02-18T01:15:26","slug":"z-ais-open-source-glm-5-achieves-record-low-hallucination-rate-and-leverages-new-rl-slime-technique","status":"publish","type":"post","link":"https:\/\/news-you-need.com\/index.php\/2026\/02\/11\/z-ais-open-source-glm-5-achieves-record-low-hallucination-rate-and-leverages-new-rl-slime-technique\/","title":{"rendered":"z.ai&#8217;s open source GLM-5 achieves record low hallucination rate and leverages new RL &#8216;slime&#8217; technique"},"content":{"rendered":"<p><a href=\"https:\/\/venturebeat.com\/technology\/z-ais-open-source-glm-5-achieves-record-low-hallucination-rate-and-leverages\">z.ai&#8217;s open source GLM-5 achieves record low hallucination rate and leverages new RL &#8216;slime&#8217; technique<\/a><\/p>\n<p><a href=\"https:\/\/venturebeat.com\/technology\/z-ais-open-source-glm-5-achieves-record-low-hallucination-rate-and-leverages\">https:\/\/venturebeat.com\/technology\/z-ais-open-source-glm-5-achieves-record-low-hallucination-rate-and-leverages<\/a><\/p>\n<p>Publish Date: <a href=\"publish_date]\">2026-02-11 19:12:00<\/a><\/p>\n<p>Source Domain: <a href=\"venturebeat.com\">venturebeat.com<\/a><\/p>\n<p>Chinese AI startup Zhupai aka z.ai is back this week with an eye-popping new frontier large language model: GLM-5.<\/p>\n<p>The latest in z.ai&#8217;s ongoing and continually impressive GLM series, it retains an open source MIT License \u2014 perfect for enterprise deployment \u2013 and, in one of several notable achievements, achieves a record-low hallucination rate on the independent Artificial Analysis Intelligence Index v4.0. <\/p>\n<p>With a score of -1 on the AA-Omniscience Index\u2014representing a massive 35-point improvement over its predecessor\u2014GLM-5 now leads the entire AI industry, including U.S. competitors like Google, OpenAI and Anthropic, in knowledge reliability by knowing when to abstain rather than fabricate information.<\/p>\n<p>Beyond its reasoning prowess, GLM-5 is built for high-utility knowledge work. It features native &#8220;Agent Mode&#8221; capabilities that allow it to turn raw prompts or source materials directly into professional office documents, including ready-to-use .docx, .pdf, and .xlsx files. <\/p>\n<p>Whether generating detailed financial reports, high school sponsorship proposals, or complex spreadsheets, GLM-5 delivers results in real-world formats that integrate directly into enterprise workflows.<\/p>\n<p>It is also disruptively priced at roughly $0.80 per million input tokens and $2.56 per million output tokens, approximately 6x cheaper than proprietary competitors like Claude Opus 4.6, making state-of-the-art agentic engineering more cost-effective than ever before. Here&#8217;s what else enterprise decision makers should know about the model and its training. <\/p>\n<h2>Technology: scaling for agentic efficiency<\/h2>\n<p>At the heart of GLM-5 is a massive leap in raw parameters. The model scales from the 355B parameters of GLM-4.5 to a staggering 744B parameters, with 40B active per token in its Mixture-of-Experts (MoE) architecture. This growth is supported by an increase in pre-training data to 28.5T tokens.<\/p>\n<p>To address training inefficiencies at this magnitude, Zai developed &#8220;slime,&#8221; a novel asynchronous&#8230;<\/p>\n<p><a href=\"https:\/\/venturebeat.com\/technology\/z-ais-open-source-glm-5-achieves-record-low-hallucination-rate-and-leverages\">Source<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"<p>z.ai&#8217;s open source GLM-5 achieves record low hallucination rate and leverages new RL &#8216;slime&#8217; technique&#8230;<\/p>\n","protected":false},"author":1,"featured_media":214684,"comment_status":"closed","ping_status":"","sticky":false,"template":"","format":"standard","meta":{"fifu_image_url":"https:\/\/images.ctfassets.net\/jdtwqhzvc2n1\/dQV83itMFRGEKiT87OEGw\/bf309d1debd7b55d3165a2c762addb20\/SZWjerB5QqmiUg-LswgV3.jpg?w=800&q=75","fifu_image_alt":"","footnotes":""},"categories":[14],"tags":[18],"class_list":["post-214683","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-artificial-intelligence","tag-large-language-model"],"_links":{"self":[{"href":"https:\/\/news-you-need.com\/index.php\/wp-json\/wp\/v2\/posts\/214683"}],"collection":[{"href":"https:\/\/news-you-need.com\/index.php\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/news-you-need.com\/index.php\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/news-you-need.com\/index.php\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/news-you-need.com\/index.php\/wp-json\/wp\/v2\/comments?post=214683"}],"version-history":[{"count":1,"href":"https:\/\/news-you-need.com\/index.php\/wp-json\/wp\/v2\/posts\/214683\/revisions"}],"predecessor-version":[{"id":214685,"href":"https:\/\/news-you-need.com\/index.php\/wp-json\/wp\/v2\/posts\/214683\/revisions\/214685"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/news-you-need.com\/index.php\/wp-json\/wp\/v2\/media\/214684"}],"wp:attachment":[{"href":"https:\/\/news-you-need.com\/index.php\/wp-json\/wp\/v2\/media?parent=214683"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/news-you-need.com\/index.php\/wp-json\/wp\/v2\/categories?post=214683"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/news-you-need.com\/index.php\/wp-json\/wp\/v2\/tags?post=214683"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}