{"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\/de\/model\/gemini-2-5-pro\/","title":{"rendered":"Gemini 2.5 Pro"},"content":{"rendered":"<p><strong>Gemini 2.5 Pro<\/strong> ist Googles DeepMind-Flaggschiff-Modell der \u201eDenk\u201c-Klasse aus der 2.5-Generation, das speziell darauf ausgelegt ist, Probleme vor der Beantwortung systematisch durchzudenken. Es deb\u00fctierte am 25. M\u00e4rz 2025 als experimenteller Preview und erreichte am 17. Juni 2025 die allgemeine Verf\u00fcgbarkeit (General Availability), wobei es sich rasch als Benchmark-F\u00fchrer im Bereich Programmierung, Mathematik und Reasoning \u00fcber lange Kontexte etablierte.<\/p>\n<p>Sein herausragendes Merkmal ist ein nativer <strong>1.048.576-Token (~1 Mio.) umfassendes Kontextfenster<\/strong> in Kombination mit vollst\u00e4ndig multimodalen Eingaben \u2013 Text, Bilder, Audio, Video und PDFs \u2013 sowie Textausgaben mit bis zu 65.536 Tokens. Adaptive \u201aDenkbudgets\u2018 erm\u00f6glichen Entwicklern, Latenz und Kosten gegen tiefere Reasoning-Kapazit\u00e4ten einzutauschen. Das Modell wird \u00fcber Google AI Studio, die Gemini-API und Vertex AI bereitgestellt; Drittanbieterzugriff erfolgt \u00fcber OpenRouter.<\/p>\n<p>Die Preise staffeln sich nach Prompt-Gr\u00f6\u00dfe: 1,25 $ pro Million Eingabetokens bis zu 200.000 Tokens, danach steigen sie auf 2,50 $; f\u00fcr Ausgabetokens betragen sie 10 $ bzw. 15 $.<\/p>\n<p><strong>Fazit:<\/strong> Gemini 2.5 Pro bleibt eine der st\u00e4rksten Wertoptionen unter den Spitzen-Reasoning-Modellen \u2013 ein echtes multimodales Kontextfenster mit einer Kapazit\u00e4t von 1 Mio. Tokens zu mittleren Preisen. Es handelt sich um ein geschlossenes Modell mit ausschlie\u00dflich API-basierter Nutzung; f\u00fcr die Analyse langer Dokumente, agentenbasierte Programmierung und Mixed-Media-Workloads ist es jedoch kaum zu schlagen. Neuere Gemini-3.x-Modelle haben es inzwischen abgel\u00f6st, doch Gemini 2.5 Pro bleibt weit verbreitet und gut unterst\u00fctzt.<\/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\/de\/wp-json\/wp\/v2\/ai_model\/1540","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/convly.ai\/de\/wp-json\/wp\/v2\/ai_model"}],"about":[{"href":"https:\/\/convly.ai\/de\/wp-json\/wp\/v2\/types\/ai_model"}],"wp:attachment":[{"href":"https:\/\/convly.ai\/de\/wp-json\/wp\/v2\/media?parent=1540"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}