{"id":1280,"date":"2026-06-23T15:00:30","date_gmt":"2026-06-23T15:00:30","guid":{"rendered":"https:\/\/convly.ai\/?p=1280"},"modified":"2026-08-01T06:46:21","modified_gmt":"2026-08-01T06:46:21","slug":"open-vs-closed-ai-cost-gap-2026","status":"publish","type":"post","link":"https:\/\/convly.ai\/fr\/open-vs-closed-ai-cost-gap-2026\/","title":{"rendered":"IA ouverte contre IA ferm\u00e9e en 2026 : l\u2019\u00e9cart r\u00e9el de co\u00fbts (nous avons \u00e9tabli les prix de 29 mod\u00e8les)"},"content":{"rendered":"<p>L\u2019IA \u00e0 poids ouverts est-elle r\u00e9ellement moins ch\u00e8re que les grandes API propri\u00e9taires \u2014 et de combien ? Nous avons recueilli les tarifs d\u2019API de l\u2019ensemble des 29 mod\u00e8les cot\u00e9s figurant dans notre <a href=\"\/fr\/models\/\">Base de donn\u00e9es de mod\u00e8les<\/a>, normalis\u00e9s chacun selon un co\u00fbt combin\u00e9 unique par million de jetons, puis regroup\u00e9s en deux cat\u00e9gories : \u00ab \u00e0 poids ouverts \u00bb et \u00ab propri\u00e9taires \u00bb. L\u2019\u00e9cart constat\u00e9 est plus important \u2014 et nettement plus constant \u2014 que ce que la plupart des gens imaginent.<\/p>\n<div class=\"convly-tldr\">\n<h3>Points cl\u00e9s<\/h3>\n<ul>\n<li><strong>Les 5 mod\u00e8les les moins chers en 2026 sont tous \u00e0 poids ouverts. Les 5 mod\u00e8les les plus co\u00fbteux sont tous propri\u00e9taires.<\/strong><\/li>\n<li>Le <strong>le co\u00fbt typique (m\u00e9dian) d\u2019un mod\u00e8le ouvert s\u2019\u00e9l\u00e8ve \u00e0 environ 0,15 $<\/strong> par million de jetons combin\u00e9s ; celui d\u2019un mod\u00e8le propri\u00e9taire atteint en moyenne <strong>~6,00 $ \u2014 soit un \u00e9cart de 39\u00d7.<\/strong><\/li>\n<li>En moyenne, les mod\u00e8les propri\u00e9taires co\u00fbtent <strong>environ 16 fois plus<\/strong> que les mod\u00e8les ouverts.<\/li>\n<li>Sur l\u2019ensemble des 29 mod\u00e8les, l\u2019\u00e9tendue totale des prix s\u2019\u00e9chelonne sur un facteur <strong>d\u2019environ 890\u00d7<\/strong> \u2014 de ~0,02 $ \u00e0 20 $ par million de jetons combin\u00e9s.<\/li>\n<li>Et cela ne tient pas compte de l\u2019auto-h\u00e9bergement, qui supprime enti\u00e8rement le co\u00fbt par jeton <em>pour les mod\u00e8les \u00e0 poids ouverts.<\/em> L\u2019\u00e9cart, r\u00e9sum\u00e9 dans un tableau<\/li>\n<\/ul>\n<\/div>\n<div id=\"ez-toc-container\" class=\"ez-toc-v2_0_86 counter-flat ez-toc-counter ez-toc-container-direction\">\n<label for=\"ez-toc-cssicon-toggle-item-6a7a0e9de0123\" class=\"ez-toc-cssicon-toggle-label\"><span class=\"\"><span class=\"eztoc-hide\" style=\"display:none;\">Basculer<\/span><span class=\"ez-toc-icon-toggle-span\"><svg style=\"fill: #000000;color:#000000\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\" class=\"list-377408\" width=\"20px\" height=\"20px\" viewbox=\"0 0 24 24\" fill=\"none\"><path d=\"M6 6H4v2h2V6zm14 0H8v2h12V6zM4 11h2v2H4v-2zm16 0H8v2h12v-2zM4 16h2v2H4v-2zm16 0H8v2h12v-2z\" fill=\"currentColor\"><\/path><\/svg><svg style=\"fill: #000000;color:#000000\" class=\"arrow-unsorted-368013\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\" width=\"10px\" height=\"10px\" viewbox=\"0 0 24 24\" version=\"1.2\" baseprofile=\"tiny\"><path d=\"M18.2 9.3l-6.2-6.3-6.2 6.3c-.2.2-.3.4-.3.7s.1.5.3.7c.2.2.4.3.7.3h11c.3 0 .5-.1.7-.3.2-.2.3-.5.3-.7s-.1-.5-.3-.7zM5.8 14.7l6.2 6.3 6.2-6.3c.2-.2.3-.5.3-.7s-.1-.5-.3-.7c-.2-.2-.4-.3-.7-.3h-11c-.3 0-.5.1-.7.3-.2.2-.3.5-.3.7s.1.5.3.7z\"\/><\/svg><\/span><\/span><\/label><input type=\"checkbox\"  id=\"ez-toc-cssicon-toggle-item-6a7a0e9de0123\"  aria-label=\"Basculer\" \/><nav><ul class='ez-toc-list ez-toc-list-level-1' ><li class='ez-toc-page-1'><a class=\"ez-toc-link ez-toc-heading-1\" href=\"https:\/\/convly.ai\/fr\/open-vs-closed-ai-cost-gap-2026\/#How_we_measured_it\" >Comment nous avons proc\u00e9d\u00e9 aux mesures<\/a><\/li><li class='ez-toc-page-1'><a class=\"ez-toc-link ez-toc-heading-2\" href=\"https:\/\/convly.ai\/fr\/open-vs-closed-ai-cost-gap-2026\/#The_gap_in_one_table\" >Les extr\u00eames parlent d\u2019eux-m\u00eames<\/a><\/li><li class='ez-toc-page-1'><a class=\"ez-toc-link ez-toc-heading-3\" href=\"https:\/\/convly.ai\/fr\/open-vs-closed-ai-cost-gap-2026\/#The_extremes_tell_the_story\" >Nuance importante : il s\u2019agit ici de co\u00fbts, non de capacit\u00e9s<\/a><\/li><li class='ez-toc-page-1'><a class=\"ez-toc-link ez-toc-heading-4\" href=\"https:\/\/convly.ai\/fr\/open-vs-closed-ai-cost-gap-2026\/#Important_nuance_this_is_cost_not_capability\" >Pourquoi cet \u00e9cart est structurel<\/a><\/li><li class='ez-toc-page-1'><a class=\"ez-toc-link ez-toc-heading-5\" href=\"https:\/\/convly.ai\/fr\/open-vs-closed-ai-cost-gap-2026\/#Why_the_gap_is_structural\" >P\u00e9rim\u00e8tre<\/a><\/li><li class='ez-toc-page-1'><a class=\"ez-toc-link ez-toc-heading-6\" href=\"https:\/\/convly.ai\/fr\/open-vs-closed-ai-cost-gap-2026\/#Bottom_line\" >Conclusion<\/a><\/li><\/ul><\/nav><\/div>\n<h2><span class=\"ez-toc-section\" id=\"How_we_measured_it\"><\/span>Comment nous avons proc\u00e9d\u00e9 aux mesures<span class=\"ez-toc-section-end\"><\/span><\/h2>\n<ul>\n<li><strong>\u2014 les 29 mod\u00e8les enti\u00e8rement couverts par la base de donn\u00e9es Convly disposant d\u2019un tarif public d\u2019API.<\/strong> (3 \u00d7 entr\u00e9e + sortie) \u00f7 4<\/li>\n<li><strong>Co\u00fbt combin\u00e9<\/strong> \u2014 <code>, ratio entr\u00e9e\/sortie de 3:1 typique du trafic r\u00e9el via API, permettant ainsi de comparer directement les mod\u00e8les dont l\u2019entr\u00e9e est peu co\u00fbteuse mais la sortie on\u00e9reuse.<\/code>\u2014 \u00ab \u00e0 poids ouverts \u00bb = poids t\u00e9l\u00e9chargeables que vous pouvez auto-h\u00e9berger (22 mod\u00e8les) ; \u00ab propri\u00e9taires \u00bb = acc\u00e8s exclusivement par API (7 mod\u00e8les).<\/li>\n<li><strong>Classification<\/strong> Sources<\/li>\n<li><strong>\u2014 tarifs d\u2019API publi\u00e9s sur OpenRouter et DeepInfra, juin 2026.<\/strong> Indicateur (co\u00fbt combin\u00e9 par million de jetons, en dollars)<\/li>\n<\/ul>\n<h2><span class=\"ez-toc-section\" id=\"The_gap_in_one_table\"><\/span>Les extr\u00eames parlent d\u2019eux-m\u00eames<span class=\"ez-toc-section-end\"><\/span><\/h2>\n<table class=\"convly-vs\">\n<thead>\n<tr>\n<th>\u00c0 poids ouverts (22)<\/th>\n<th>Propri\u00e9taires (7)<\/th>\n<th>Proprietary (7)<\/th>\n<th>\u00c9cart<\/th>\n<\/tr>\n<\/thead>\n<tbody>\n<tr>\n<td><strong>Moyenne<\/strong><\/td>\n<td>$0.50<\/td>\n<td>$8.16<\/td>\n<td><strong>16\u00d7<\/strong><\/td>\n<\/tr>\n<tr>\n<td><strong>M\u00e9diane (mod\u00e8le typique)<\/strong><\/td>\n<td>$0.15<\/td>\n<td>$6.00<\/td>\n<td><strong>39\u00d7<\/strong><\/td>\n<\/tr>\n<tr>\n<td>Moins cher du groupe<\/td>\n<td>0,02 $ (Llama 3.1 8B)<\/td>\n<td>2,00 $ (Claude Haiku 4.5)<\/td>\n<td>\u2014<\/td>\n<\/tr>\n<tr>\n<td>Plus cher du groupe<\/td>\n<td>3,00 $ (Mistral Large 3)<\/td>\n<td>20,00 $ (Claude Fable 5)<\/td>\n<td>\u2014<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<h2><span class=\"ez-toc-section\" id=\"The_extremes_tell_the_story\"><\/span>Nuance importante : il s\u2019agit ici de co\u00fbts, non de capacit\u00e9s<span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p>Triant les 29 mod\u00e8les selon leur co\u00fbt combin\u00e9, le sch\u00e9ma est frappant : les mod\u00e8les open-weight dominent le bas du classement, tandis que les mod\u00e8les propri\u00e9taires occupent le haut :<\/p>\n<table class=\"convly-vs\">\n<thead>\n<tr>\n<th>5 mod\u00e8les les moins chers (tous open-weight)<\/th>\n<th>Co\u00fbt combin\u00e9 par million de dollars<\/th>\n<th>5 mod\u00e8les les plus chers (tous propri\u00e9taires)<\/th>\n<th>Co\u00fbt combin\u00e9 par million de dollars<\/th>\n<\/tr>\n<\/thead>\n<tbody>\n<tr>\n<td>Llama 3.1 8B<\/td>\n<td>$0.02<\/td>\n<td>Claude Fable 5<\/td>\n<td>$20.00<\/td>\n<\/tr>\n<tr>\n<td>Mistral 7B<\/td>\n<td>$0.02<\/td>\n<td>GPT-5.5<\/td>\n<td>$11.25<\/td>\n<\/tr>\n<tr>\n<td>Mistral NeMo 12B<\/td>\n<td>$0.03<\/td>\n<td>Claude Opus 4.8<\/td>\n<td>$10.00<\/td>\n<\/tr>\n<tr>\n<td>Gemma 3 4B<\/td>\n<td>$0.06<\/td>\n<td>Claude Sonnet 4.6<\/td>\n<td>$6.00<\/td>\n<\/tr>\n<tr>\n<td>Qwen3 8B<\/td>\n<td>$0.07<\/td>\n<td>Gemini 3.1 Pro<\/td>\n<td>$4.50<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<p>Aucun mod\u00e8le propri\u00e9taire ne figure dans le tiers inf\u00e9rieur du march\u00e9, et aucun mod\u00e8le open-weight ne figure dans le tiers sup\u00e9rieur. La zone de chevauchement est \u00e9troite : le mod\u00e8le propri\u00e9taire le moins cher (Claude Haiku 4.5, 2,00 $) se situe juste en dessous du mod\u00e8le open-weight le plus cher (Mistral Large 3, 3,00 $).<\/p>\n<h2><span class=\"ez-toc-section\" id=\"Important_nuance_this_is_cost_not_capability\"><\/span>Pourquoi cet \u00e9cart est structurel<span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p>Les mod\u00e8les les plus co\u00fbteux conservent toutefois une avance sur les t\u00e2ches de raisonnement et d\u2019agence les plus complexes. Dans notre indicateur compl\u00e9mentaire <a href=\"\/fr\/ai-price-performance-index-2026\/\">Indice AI Prix-Performance<\/a> nous avons constat\u00e9 que la prime associ\u00e9e aux mod\u00e8les de pointe permet d\u2019acqu\u00e9rir les <em>derniers points<\/em> d\u2019intelligence, et non une valeur proportionnelle. Toutefois, pour la grande majorit\u00e9 des charges de production \u2014 classification, extraction, RAG, synth\u00e8se, chat \u2014 l\u2019\u00e9cart de capacit\u00e9 entre un bon mod\u00e8le open-weight et un mod\u00e8le de pointe est bien moindre que l\u2019\u00e9cart de prix de 39\u00d7. Vous payez souvent 39\u00d7 davantage pour les 10 \u00e0 20 % finaux de capacit\u00e9 dont vous n\u2019avez probablement pas besoin.<\/p>\n<h2><span class=\"ez-toc-section\" id=\"Why_the_gap_is_structural\"><\/span>P\u00e9rim\u00e8tre<span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p>This isn&#8217;t a temporary discount war. Intense open-weight competition \u2014 Qwen, Llama, Gemma, DeepSeek and Mistral all shipping strong models under permissive licenses \u2014 has driven the price floor toward zero. Meanwhile frontier labs price for peak capability and enterprise willingness-to-pay. The result is a market that is bifurcating: a race-to-zero floor and a premium ceiling, with a widening canyon between them.<\/p>\n<h2><span class=\"ez-toc-section\" id=\"Bottom_line\"><\/span>Conclusion<span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p>Pour les d\u00e9ploiements de production sensibles aux co\u00fbts, un mod\u00e8le open-weight ou interm\u00e9diaire constitue le choix rationnel par d\u00e9faut en 2026 \u2014 et l\u2019h\u00e9bergement priv\u00e9 \u00e9limine totalement le co\u00fbt par jeton (d\u00e9couvrez ce que votre GPU peut ex\u00e9cuter gr\u00e2ce \u00e0 notre <a href=\"\/fr\/llm-vram-calculator\/\">Calculateur de VRAM<\/a>). R\u00e9servez les mod\u00e8les propri\u00e9taires de pointe aux t\u00e2ches v\u00e9ritablement les plus complexes. Analysez vos propres besoins \u00e0 l\u2019aide de notre <a href=\"\/fr\/ai-api-cost-calculator\/\">Calculateur des co\u00fbts d\u2019API<\/a> pour obtenir vos chiffres exacts.<\/p>\n<p><em>Data: Convly <a href=\"https:\/\/convly.ai\/fr\/models\/\">Base de donn\u00e9es des mod\u00e8les IA<\/a> (API pricing via OpenRouter and DeepInfra). Blended cost uses a 3:1 input:output ratio. Figures current as of June 2026.<\/em><\/p>","protected":false},"excerpt":{"rendered":"<p>We priced all 29 models in our database and split them open vs proprietary. The 5 cheapest are all open-weight; the 5 most expensive all proprietary. The typical gap: 39\u00d7.<\/p>","protected":false},"author":1,"featured_media":1903,"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":[247],"tags":[813,421,454,745,423,812],"class_list":["post-1280","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-ai-benchmarks","tag-cost-analysis","tag-deepseek","tag-llama","tag-llm-pricing","tag-open-source-ai","tag-open-vs-closed"],"_links":{"self":[{"href":"https:\/\/convly.ai\/fr\/wp-json\/wp\/v2\/posts\/1280","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=1280"}],"version-history":[{"count":2,"href":"https:\/\/convly.ai\/fr\/wp-json\/wp\/v2\/posts\/1280\/revisions"}],"predecessor-version":[{"id":1881,"href":"https:\/\/convly.ai\/fr\/wp-json\/wp\/v2\/posts\/1280\/revisions\/1881"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/convly.ai\/fr\/wp-json\/wp\/v2\/media\/1903"}],"wp:attachment":[{"href":"https:\/\/convly.ai\/fr\/wp-json\/wp\/v2\/media?parent=1280"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/convly.ai\/fr\/wp-json\/wp\/v2\/categories?post=1280"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/convly.ai\/fr\/wp-json\/wp\/v2\/tags?post=1280"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}