{"id":1260,"date":"2026-06-23T14:45:03","date_gmt":"2026-06-23T14:45:03","guid":{"rendered":"https:\/\/convly.ai\/?p=1260"},"modified":"2026-06-23T14:45:03","modified_gmt":"2026-06-23T14:45:03","slug":"qwen3-235b-a22b-vs-glm-5-2","status":"publish","type":"post","link":"https:\/\/convly.ai\/it\/qwen3-235b-a22b-vs-glm-5-2\/","title":{"rendered":"Qwen3 235B-A22B vs GLM 5.2: specifiche tecniche, prezzi e quale scegliere (2026)"},"content":{"rendered":"<p><strong>Qwen3 235B-A22B<\/strong> vs <strong>GLM 5.2<\/strong> \u2014 Il modello di punta open source di Alibaba contro quello di Zhipu. Di seguito il confronto completo: specifiche tecniche, prezzi delle API, finestra contestuale, requisiti hardware per l\u2019esecuzione locale e una raccomandazione chiara, basata sui dati, su quale scegliere.<\/p>\n<div class=\"cmp\">\n  <table class=\"cmp-table\">\n    <thead><tr><th>Specifiche<\/th><th><a href=\"https:\/\/convly.ai\/it\/model\/qwen3-235b-a22b\/\">Qwen3 235B-A22B<\/a><\/th><th><a href=\"https:\/\/convly.ai\/it\/model\/glm-5-2\/\">GLM 5.2<\/a><\/th><\/tr><\/thead>\n    <tbody>\n          <tr><td class=\"cmp-spec\">Sviluppatore<\/td><td class=\"\">Alibaba<\/td><td class=\"\">Zhipu AI<\/td><\/tr>\n          <tr><td class=\"cmp-spec\">Tipo<\/td><td class=\"\">LLM (MoE)<\/td><td class=\"\">LLM (per programmazione\/agenti, MoE)<\/td><\/tr>\n          <tr><td class=\"cmp-spec\">Parametri<\/td><td class=\"\">235 miliardi totali \/ 22 miliardi attivi (MoE)<\/td><td class=\"\">744 miliardi totali \/ ~40 miliardi attivi (MoE)<\/td><\/tr>\n          <tr><td class=\"cmp-spec\">Finestra contestuale<\/td><td class=\"\">128K<\/td><td class=\"cmp-win\">1 milione<\/td><\/tr>\n          <tr><td class=\"cmp-spec\">Modalit\u00e0<\/td><td class=\"\">Testo \u2192 Testo<\/td><td class=\"\">Testo \u2192 Testo<\/td><\/tr>\n          <tr><td class=\"cmp-spec\">Licenza<\/td><td class=\"\">Apache 2.0 (open)<\/td><td class=\"\">MIT (open)<\/td><\/tr>\n          <tr><td class=\"cmp-spec\">Pesi aperti<\/td><td class=\"\">\u2705 S\u00ec<\/td><td class=\"\">\u2705 S\u00ec<\/td><\/tr>\n          <tr><td class=\"cmp-spec\">Costo input ($\/1 milione)<\/td><td class=\"cmp-win\">$0.45<\/td><td class=\"\">$1.4<\/td><\/tr>\n          <tr><td class=\"cmp-spec\">Costo output ($\/1 milione)<\/td><td class=\"\">$1.8<\/td><td class=\"\">$4.4<\/td><\/tr>\n          <tr><td class=\"cmp-spec\">VRAM (4 bit)<\/td><td class=\"\">~140 GB<\/td><td class=\"\">~370 GB<\/td><\/tr>\n          <tr><td class=\"cmp-spec\">GPU minima (locale)<\/td><td class=\"\">Multi-GPU o Mac con 192 GB<\/td><td class=\"\">Server multi-GPU (es. 5\u00d7 H100 da 80 GB)<\/td><\/tr>\n          <tr><td class=\"cmp-spec\">Data di rilascio<\/td><td class=\"\">2025<\/td><td class=\"\">2026-06<\/td><\/tr>\n        <\/tbody>\n  <\/table>\n\n    <div class=\"cmp-verdict\">\n    <h3>Principali differenze<\/h3>\n    <ul><li><strong>Costo:<\/strong> Qwen3 235B-A22B \u00e8 <strong>Il 173% pi\u00f9 economico<\/strong> than GLM 5.2 on a blended-token basis.<\/li><li><strong>Contesto:<\/strong> GLM 5.2 vince per quanto riguarda la finestra contestuale (1 milione di token rispetto a 128K), risultando quindi pi\u00f9 adatto per documenti lunghi, grandi codebase e input RAG estesi.<\/li><li><strong>Apertura:<\/strong> entrambi hanno pesi aperti, quindi entrambi possono essere ospitati autonomamente o sottoposti a fine-tuning. Confronta le esigenze di VRAM indicate sopra per verificare quali modelli la tua GPU \u00e8 in grado di eseguire.<\/li><li><strong>Esegui Qwen3 235B-A22B localmente:<\/strong> ~~140 GB a 4 bit (minimo per pi\u00f9 GPU o Mac con 192 GB).<\/li><li><strong>Esegui GLM 5.2 localmente:<\/strong> ~~370 GB a 4 bit (minimo server multi-GPU, ad es. 5\u00d7 H100 da 80 GB).<\/li><\/ul>\n  <\/div>\n\n    <div class=\"cmp-rec\">\n    <h3>Quale scegliere?<\/h3>\n    <p><strong>Scegli Qwen3 235B-A22B<\/strong> se desideri un costo per token pi\u00f9 basso per carichi di lavoro ad alto volume.<\/p>\n    <p><strong>Scegli GLM 5.2<\/strong> se hai bisogno di una finestra contestuale pi\u00f9 ampia.<\/p>\n    <p class=\"cmp-tools\">\u2192 Stima i costi reali con il <a href=\"\/it\/ai-api-cost-calculator\/\">Calcolatore costi API<\/a> \u00b7 verifica l'hardware locale con il <a href=\"\/it\/llm-vram-calculator\/\">Calcolatore VRAM<\/a> \u00b7 esplora tutti i <a href=\"\/it\/models\/\">30+ modelli<\/a>.<\/p>\n  <\/div>\n<\/div>\n\n<p>Tutte le specifiche e i prezzi sono recuperati in tempo reale dal nostro <a href=\"\/it\/models\/\">Database di modelli AI<\/a> e mantenuti aggiornati. Confronta uno qualsiasi dei due modelli con altri oppure stima la tua spesa mensile con i calcolatori gratuiti sopra indicati.<\/p>","protected":false},"excerpt":{"rendered":"<p>Qwen3 235B-A22B vs GLM 5.2 compared: specs, API pricing, context window, VRAM and a clear verdict on which model to choose in 2026.<\/p>","protected":false},"author":1,"featured_media":0,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"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":""},"categories":[246],"tags":[395,764,796],"class_list":["post-1260","post","type-post","status-publish","format-standard","hentry","category-ai-comparisons","tag-ai-model-comparison","tag-glm-5-2","tag-qwen3-235b-a22b"],"_links":{"self":[{"href":"https:\/\/convly.ai\/it\/wp-json\/wp\/v2\/posts\/1260","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/convly.ai\/it\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/convly.ai\/it\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/convly.ai\/it\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/convly.ai\/it\/wp-json\/wp\/v2\/comments?post=1260"}],"version-history":[{"count":0,"href":"https:\/\/convly.ai\/it\/wp-json\/wp\/v2\/posts\/1260\/revisions"}],"wp:attachment":[{"href":"https:\/\/convly.ai\/it\/wp-json\/wp\/v2\/media?parent=1260"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/convly.ai\/it\/wp-json\/wp\/v2\/categories?post=1260"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/convly.ai\/it\/wp-json\/wp\/v2\/tags?post=1260"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}