{"id":1266,"date":"2026-06-23T14:45:03","date_gmt":"2026-06-23T14:45:03","guid":{"rendered":"https:\/\/convly.ai\/?p=1266"},"modified":"2026-06-23T14:45:03","modified_gmt":"2026-06-23T14:45:03","slug":"deepseek-v4-flash-vs-gemini-3-5-flash","status":"publish","type":"post","link":"https:\/\/convly.ai\/de\/deepseek-v4-flash-vs-gemini-3-5-flash\/","title":{"rendered":"DeepSeek V4-Flash vs. Gemini 3.5 Flash: Spezifikationen, Preise &amp; Entscheidungshilfe (2026)"},"content":{"rendered":"<p><strong>DeepSeek V4-Flash<\/strong> vs. <strong>Gemini 3.5 Flash<\/strong> \u2013 die beiden g\u00fcnstigsten schnellen Modelle im direkten Kostenvergleich. Im Folgenden finden Sie den vollst\u00e4ndigen Vergleich: Spezifikationen, API-Preise, Kontextfenster, lokale Hardware-Anforderungen sowie eine klare, datengest\u00fctzte Empfehlung, welches Modell Sie w\u00e4hlen sollten.<\/p>\n<div class=\"cmp\">\n  <table class=\"cmp-table\">\n    <thead><tr><th>Spezifikation<\/th><th><a href=\"https:\/\/convly.ai\/de\/model\/deepseek-v4-flash\/\">DeepSeek V4-Flash<\/a><\/th><th><a href=\"https:\/\/convly.ai\/de\/model\/gemini-3-5-flash\/\">Gemini 3.5 Flash<\/a><\/th><\/tr><\/thead>\n    <tbody>\n          <tr><td class=\"cmp-spec\">Entwickler<\/td><td class=\"\">DeepSeek<\/td><td class=\"\">Google<\/td><\/tr>\n          <tr><td class=\"cmp-spec\">Typ<\/td><td class=\"\">LLM (MoE)<\/td><td class=\"\">LLM (multimodal)<\/td><\/tr>\n          <tr><td class=\"cmp-spec\">Parameter<\/td><td class=\"\">284 Mrd. insgesamt \/ ~13 Mrd. aktiv (MoE)<\/td><td class=\"\">Nicht offengelegt<\/td><\/tr>\n          <tr><td class=\"cmp-spec\">Kontextfenster<\/td><td class=\"\">1 Mio.<\/td><td class=\"\">1 Mio.<\/td><\/tr>\n          <tr><td class=\"cmp-spec\">Modalit\u00e4t<\/td><td class=\"\">Text \u2192 Text<\/td><td class=\"\">Text, Bild, Audio, Video \u2192 Text<\/td><\/tr>\n          <tr><td class=\"cmp-spec\">Lizenz<\/td><td class=\"\">MIT (offen)<\/td><td class=\"\">Propriet\u00e4r<\/td><\/tr>\n          <tr><td class=\"cmp-spec\">Offene Gewichte<\/td><td class=\"\">\u2705 Ja<\/td><td class=\"\">\u274c Nein<\/td><\/tr>\n          <tr><td class=\"cmp-spec\">Eingabepreis (US$\/1 Mio.)<\/td><td class=\"cmp-win\">$0.14<\/td><td class=\"\">$1.50<\/td><\/tr>\n          <tr><td class=\"cmp-spec\">Ausgabepreis (US$\/1 Mio.)<\/td><td class=\"\">$0.28<\/td><td class=\"\">$9.00<\/td><\/tr>\n          <tr><td class=\"cmp-spec\">VRAM (4-Bit)<\/td><td class=\"\">~140 GB<\/td><td class=\"\">\u2014<\/td><\/tr>\n          <tr><td class=\"cmp-spec\">Mindest-GPU (lokal)<\/td><td class=\"\">2\u00d7 H100 80 GB (4-Bit)<\/td><td class=\"\">\u2014<\/td><\/tr>\n          <tr><td class=\"cmp-spec\">Ver\u00f6ffentlichung<\/td><td class=\"\">2026-04<\/td><td class=\"\">2026<\/td><\/tr>\n        <\/tbody>\n  <\/table>\n\n    <div class=\"cmp-verdict\">\n    <h3>Wesentliche Unterschiede<\/h3>\n    <ul><li><strong>Kosten:<\/strong> DeepSeek V4-Flash ist <strong>1829 % g\u00fcnstiger<\/strong> als Gemini 3.5 Flash auf Basis eines gemischten Token-Preises.<\/li><li><strong>Offenheit:<\/strong> DeepSeek V4-Flash verf\u00fcgt \u00fcber offene Gewichte (selbsthostbar, privat, feinjustierbar); Gemini 3.5 Flash ist propriet\u00e4r (ausschlie\u00dflich \u00fcber API nutzbar, aber vollst\u00e4ndig verwaltet).<\/li><li><strong>DeepSeek V4-Flash lokal ausf\u00fchren:<\/strong> ~~140 GB bei 4-Bit-Quantisierung (mindestens 2\u00d7 H100 80 GB (4-Bit)).<\/li><\/ul>\n  <\/div>\n\n    <div class=\"cmp-rec\">\n    <h3>Welches Modell sollten Sie w\u00e4hlen?<\/h3>\n    <p><strong>W\u00e4hlen Sie DeepSeek V4-Flash<\/strong> wenn Sie geringere Kosten pro Token bei Hochvolumen-Workloads bevorzugen, wenn Sie die Modelle selbst hosten oder feinjustieren m\u00f6chten oder Ihre Daten vollst\u00e4ndig vertraulich halten wollen.<\/p>\n    <p><strong>W\u00e4hlen Sie Gemini 3.5 Flash<\/strong> wenn Sie eine vollst\u00e4ndig verwaltete API ohne eigene Infrastruktur bevorzugen.<\/p>\n    <p class=\"cmp-tools\">\u2192 Sch\u00e4tzen Sie die tats\u00e4chlichen Kosten mit dem <a href=\"\/de\/ai-api-cost-calculator\/\">API-Kostenrechner<\/a> \u00b7 pr\u00fcfen Sie Ihre lokale Hardware mit dem <a href=\"\/de\/llm-vram-calculator\/\">VRAM-Rechner<\/a> \u00b7 durchsuchen Sie alle <a href=\"\/de\/models\/\">\u00fcber 30 Modelle<\/a>.<\/p>\n  <\/div>\n<\/div>\n\n<p>Alle Spezifikationen und Preise werden live aus unserer <a href=\"\/de\/models\/\">Datenbank f\u00fcr KI-Modelle<\/a> Datenbank abgerufen und stets aktuell gehalten. Vergleichen Sie entweder eines der beiden Modelle mit anderen oder sch\u00e4tzen Sie Ihre eigenen monatlichen Ausgaben mithilfe der oben genannten kostenlosen Rechner.<\/p>","protected":false},"excerpt":{"rendered":"<p>DeepSeek V4-Flash vs Gemini 3.5 Flash 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":[395,797,798],"class_list":["post-1266","post","type-post","status-publish","format-standard","hentry","category-ai-comparisons","tag-ai-model-comparison","tag-deepseek-v4-flash","tag-gemini-3-5-flash"],"_links":{"self":[{"href":"https:\/\/convly.ai\/de\/wp-json\/wp\/v2\/posts\/1266","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/convly.ai\/de\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/convly.ai\/de\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/convly.ai\/de\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/convly.ai\/de\/wp-json\/wp\/v2\/comments?post=1266"}],"version-history":[{"count":0,"href":"https:\/\/convly.ai\/de\/wp-json\/wp\/v2\/posts\/1266\/revisions"}],"wp:attachment":[{"href":"https:\/\/convly.ai\/de\/wp-json\/wp\/v2\/media?parent=1266"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/convly.ai\/de\/wp-json\/wp\/v2\/categories?post=1266"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/convly.ai\/de\/wp-json\/wp\/v2\/tags?post=1266"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}