{"id":1540,"date":"2026-07-11T17:46:27","date_gmt":"2026-07-11T17:46:27","guid":{"rendered":"https:\/\/convly.ai\/model\/gemini-2-5-pro\/"},"modified":"2026-07-11T17:46:27","modified_gmt":"2026-07-11T17:46:27","slug":"gemini-2-5-pro","status":"publish","type":"ai_model","link":"https:\/\/convly.ai\/fr\/model\/gemini-2-5-pro\/","title":{"rendered":"Gemini 2.5 Pro"},"content":{"rendered":"<p><strong>Gemini 2.5 Pro<\/strong> est le mod\u00e8le phare \u00ab r\u00e9fl\u00e9chissant \u00bb de Google DeepMind issu de la g\u00e9n\u00e9ration 2.5, con\u00e7u pour analyser les probl\u00e8mes de fa\u00e7on approfondie avant de fournir une r\u00e9ponse. Il a fait sa premi\u00e8re apparition en version exp\u00e9rimentale le 25 mars 2025, puis est pass\u00e9 en disponibilit\u00e9 g\u00e9n\u00e9rale le 17 juin 2025, s\u2019imposant rapidement comme une r\u00e9f\u00e9rence dans les domaines du codage, des math\u00e9matiques et du raisonnement sur des contextes longs.<\/p>\n<p>Sa fonctionnalit\u00e9 phare est une fen\u00eatre de contexte native <strong>de 1 048 576 jetons (environ 1 million)<\/strong> associ\u00e9e \u00e0 une entr\u00e9e pleinement multimodale \u2014 texte, images, audio, vid\u00e9o et fichiers PDF \u2014 et \u00e0 une sortie textuelle pouvant atteindre 65 536 jetons. Des budgets de \u00ab r\u00e9flexion \u00bb adaptatifs permettent aux d\u00e9veloppeurs d\u2019\u00e9changer latence et co\u00fbt contre une profondeur accrue du raisonnement. Le mod\u00e8le est accessible via Google AI Studio, l\u2019API Gemini et Vertex AI, ainsi que par l\u2019interm\u00e9diaire de tiers tels qu\u2019OpenRouter.<\/p>\n<p>Les tarifs sont segment\u00e9s selon la taille des prompts : 1,25 $ par million de jetons d\u2019entr\u00e9e jusqu\u2019\u00e0 200 K, puis 2,50 $ au-del\u00e0 de ce seuil ; les jetons de sortie sont factur\u00e9s 10 $ ou 15 $ respectivement.<\/p>\n<p><strong>Verdict :<\/strong> Gemini 2.5 Pro reste l\u2019un des mod\u00e8les de raisonnement de pointe offrant le meilleur rapport qualit\u00e9-prix \u2014 une fen\u00eatre de contexte multimodale v\u00e9ritablement \u00e9tendue \u00e0 1 million de jetons, propos\u00e9e \u00e0 un prix interm\u00e9diaire. Il s\u2019agit d\u2019un mod\u00e8le \u00e0 poids ferm\u00e9s, accessible uniquement par API ; toutefois, pour l\u2019analyse de documents longs, le d\u00e9veloppement d\u2019agents intelligents ou les charges de travail multim\u00e9dias, il est difficile \u00e0 battre. Les mod\u00e8les Gemini 3.x plus r\u00e9cents l\u2019ont d\u00e9sormais remplac\u00e9, mais Gemini 2.5 Pro demeure largement d\u00e9ploy\u00e9 et bien pris en charge.<\/p>","protected":false},"excerpt":{"rendered":"<p>Gemini 2.5 Pro is Google DeepMind&#8217;s flagship &#8220;thinking&#8221; model from the 2.5 generation, built to reason through problems before it [&hellip;]<\/p>\n","protected":false},"featured_media":0,"template":"","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":""}},"cm_developer":"Google (Google DeepMind)","cm_model_type":"LLM (frontier reasoning \/ thinking)","cm_modality":"Text, Image, Audio, Video, PDF \u2192 Text","cm_parameters":"Undisclosed","cm_context_window":"1M (1,048,576 tokens)","cm_max_output":"64K (65,536 tokens)","cm_license":"Proprietary","cm_open_weights":"no","cm_release_date":"March 2025 (preview); June 17, 2025 (GA)","cm_input_price":"1.25","cm_output_price":"10","cm_api_providers":"Google AI Studio (Gemini API), Vertex AI, OpenRouter","cm_vram_fp16":"","cm_vram_q4":"","cm_min_gpu":"","cm_benchmarks":"","cm_official_url":"https:\/\/ai.google.dev\/gemini-api\/docs\/models#gemini-2.5-pro"},"class_list":["post-1540","ai_model","type-ai_model","status-publish","hentry"],"_links":{"self":[{"href":"https:\/\/convly.ai\/fr\/wp-json\/wp\/v2\/ai_model\/1540","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/convly.ai\/fr\/wp-json\/wp\/v2\/ai_model"}],"about":[{"href":"https:\/\/convly.ai\/fr\/wp-json\/wp\/v2\/types\/ai_model"}],"wp:attachment":[{"href":"https:\/\/convly.ai\/fr\/wp-json\/wp\/v2\/media?parent=1540"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}