{"id":1265,"date":"2026-06-23T14:45:03","date_gmt":"2026-06-23T14:45:03","guid":{"rendered":"https:\/\/convly.ai\/?p=1265"},"modified":"2026-06-23T14:45:03","modified_gmt":"2026-06-23T14:45:03","slug":"qwen3-235b-a22b-vs-gpt-5-5","status":"publish","type":"post","link":"https:\/\/convly.ai\/fr\/qwen3-235b-a22b-vs-gpt-5-5\/","title":{"rendered":"Qwen3 235B-A22B contre GPT-5.5 : sp\u00e9cifications, tarifs et choix (2026)"},"content":{"rendered":"<p><strong>Qwen3 235B-A22B<\/strong> contre <strong>GPT-5.5<\/strong> \u2014 un mod\u00e8le phare ouvert face \u00e0 la r\u00e9f\u00e9rence d\u2019OpenAI. Voici ci-dessous une comparaison d\u00e9taill\u00e9e : sp\u00e9cifications techniques, tarifs d\u2019API, fen\u00eatre de contexte, exigences mat\u00e9rielles locales et recommandation claire, fond\u00e9e sur des donn\u00e9es objectives, quant au mod\u00e8le \u00e0 privil\u00e9gier.<\/p>\n<div class=\"cmp\">\n  <table class=\"cmp-table\">\n    <thead><tr><th>Sp\u00e9cifications<\/th><th><a href=\"https:\/\/convly.ai\/fr\/model\/qwen3-235b-a22b\/\">Qwen3 235B-A22B<\/a><\/th><th><a href=\"https:\/\/convly.ai\/fr\/model\/gpt-5-5\/\">GPT-5.5<\/a><\/th><\/tr><\/thead>\n    <tbody>\n          <tr><td class=\"cmp-spec\">D\u00e9veloppeur<\/td><td class=\"\">Alibaba<\/td><td class=\"\">OpenAI<\/td><\/tr>\n          <tr><td class=\"cmp-spec\">Type<\/td><td class=\"\">LLM (architecture MoE)<\/td><td class=\"\">LLM (raisonnement)<\/td><\/tr>\n          <tr><td class=\"cmp-spec\">Param\u00e8tres<\/td><td class=\"\">235 milliards au total \/ 22 milliards actifs (MoE)<\/td><td class=\"\">Non divulgu\u00e9<\/td><\/tr>\n          <tr><td class=\"cmp-spec\">Fen\u00eatre de contexte<\/td><td class=\"\">128 K<\/td><td class=\"cmp-win\">1,05 million<\/td><\/tr>\n          <tr><td class=\"cmp-spec\">Modalit\u00e9<\/td><td class=\"\">Texte \u2192 Texte<\/td><td class=\"\">Texte, vision \u2192 texte<\/td><\/tr>\n          <tr><td class=\"cmp-spec\">Licence<\/td><td class=\"\">Apache 2.0 (ouverte)<\/td><td class=\"\">Propri\u00e9taire<\/td><\/tr>\n          <tr><td class=\"cmp-spec\">Poids ouverts<\/td><td class=\"\">\u2705 Yes<\/td><td class=\"\">\u274c No<\/td><\/tr>\n          <tr><td class=\"cmp-spec\">Co\u00fbt d\u2019entr\u00e9e (en $\/million)<\/td><td class=\"cmp-win\">$0.45<\/td><td class=\"\">$5.00<\/td><\/tr>\n          <tr><td class=\"cmp-spec\">Co\u00fbt de sortie (en $\/million)<\/td><td class=\"\">$1.8<\/td><td class=\"\">$30.00<\/td><\/tr>\n          <tr><td class=\"cmp-spec\">VRAM (4 bits)<\/td><td class=\"\">~140 Go<\/td><td class=\"\">\u2014<\/td><\/tr>\n          <tr><td class=\"cmp-spec\">GPU minimal requis (en local)<\/td><td class=\"\">Multi-GPU ou Mac avec 192 Go<\/td><td class=\"\">\u2014<\/td><\/tr>\n          <tr><td class=\"cmp-spec\">Publi\u00e9<\/td><td class=\"\">2025<\/td><td class=\"\">2026<\/td><\/tr>\n        <\/tbody>\n  <\/table>\n\n    <div class=\"cmp-verdict\">\n    <h3>Principales diff\u00e9rences<\/h3>\n    <ul><li><strong>Co\u00fbt :<\/strong> Qwen3 235B-A22B est <strong>1 329 % moins cher<\/strong> que le GPT-5.5 sur une base de co\u00fbt par jeton pond\u00e9r\u00e9.<\/li><li><strong>Contexte :<\/strong> Le GPT-5.5 se distingue par sa fen\u00eatre de contexte (1,05 million contre 128 K) \u2014 id\u00e9al pour les documents longs, les grands bases de code et les entr\u00e9es volumineuses RAG.<\/li><li><strong>Ouverture :<\/strong> Qwen3 235B-A22B dispose de poids ouverts (h\u00e9bergement local possible, confidentialit\u00e9 garantie, adaptation autoris\u00e9e) ; le GPT-5.5 est propri\u00e9taire (acc\u00e8s uniquement via API, mais enti\u00e8rement g\u00e9r\u00e9).<\/li><li><strong>Ex\u00e9cutez Qwen3 235B-A22B localement :<\/strong> ~~140 Go en 4 bits (minimum pour plusieurs GPU ou Mac avec 192 Go de m\u00e9moire).<\/li><\/ul>\n  <\/div>\n\n    <div class=\"cmp-rec\">\n    <h3>Lequel choisir ?<\/h3>\n    <p><strong>Choisissez Qwen3 235B-A22B<\/strong> si vous recherchez un co\u00fbt inf\u00e9rieur par jeton pour des charges de travail \u00e0 fort volume, ou si vous souhaitez h\u00e9berger le mod\u00e8le localement, l\u2019ajuster finement ou garantir une confidentialit\u00e9 totale des donn\u00e9es.<\/p>\n    <p><strong>Choisissez GPT-5.5<\/strong> si vous avez besoin d\u2019une fen\u00eatre de contexte plus grande, ou si vous pr\u00e9f\u00e9rez une API enti\u00e8rement g\u00e9r\u00e9e sans infrastructure \u00e0 exploiter.<\/p>\n    <p class=\"cmp-tools\">\u2192 Estimez les co\u00fbts r\u00e9els avec le <a href=\"\/fr\/ai-api-cost-calculator\/\">Calculateur des co\u00fbts d\u2019API<\/a> \u00b7 v\u00e9rifiez la compatibilit\u00e9 de votre mat\u00e9riel local avec le <a href=\"\/fr\/llm-vram-calculator\/\">Calculateur de VRAM<\/a> \u00b7 parcourez l\u2019ensemble des <a href=\"\/fr\/models\/\">30+ mod\u00e8les<\/a>.<\/p>\n  <\/div>\n<\/div>\n\n<p>Toutes les sp\u00e9cifications et les prix sont r\u00e9cup\u00e9r\u00e9s en temps r\u00e9el depuis notre <a href=\"\/fr\/models\/\">Base de donn\u00e9es des mod\u00e8les IA<\/a> et r\u00e9guli\u00e8rement mis \u00e0 jour. Comparez l'un ou l'autre de ces mod\u00e8les avec d'autres, ou estimez votre d\u00e9pense mensuelle gr\u00e2ce aux calculateurs gratuits ci-dessus.<\/p>","protected":false},"excerpt":{"rendered":"<p>Qwen3 235B-A22B vs GPT-5.5 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":1918,"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":[395,654,796],"class_list":["post-1265","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-ai-comparisons","tag-ai-model-comparison","tag-gpt-5-5","tag-qwen3-235b-a22b"],"_links":{"self":[{"href":"https:\/\/convly.ai\/fr\/wp-json\/wp\/v2\/posts\/1265","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/convly.ai\/fr\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/convly.ai\/fr\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/convly.ai\/fr\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/convly.ai\/fr\/wp-json\/wp\/v2\/comments?post=1265"}],"version-history":[{"count":0,"href":"https:\/\/convly.ai\/fr\/wp-json\/wp\/v2\/posts\/1265\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/convly.ai\/fr\/wp-json\/wp\/v2\/media\/1918"}],"wp:attachment":[{"href":"https:\/\/convly.ai\/fr\/wp-json\/wp\/v2\/media?parent=1265"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/convly.ai\/fr\/wp-json\/wp\/v2\/categories?post=1265"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/convly.ai\/fr\/wp-json\/wp\/v2\/tags?post=1265"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}