[{"data":1,"prerenderedAt":991},["ShallowReactive",2],{"/de-de/blog/optimize-with-open-weight-models":3,"navigation-de-de":245,"banner-de-de":671,"footer-de-de":678,"blog-post-authors-de-de-Brittany Lutz":934,"blog-related-posts-de-de-optimize-with-open-weight-models":948,"blog-share-wrapper-de-de":970,"next-steps-de-de":981},{"id":4,"title":5,"authors":6,"body":8,"category":224,"date":225,"description":226,"extension":227,"externalUrl":228,"faq":228,"featured":229,"heroImage":230,"meta":231,"navigation":232,"path":233,"seo":234,"slug":237,"stem":238,"tags":239,"template":243,"updatedDate":228,"__hash__":244},"blogPosts/de-de/blog/optimize-with-open-weight-models.md","Preis-Leistung optimieren – mit gehosteten Open-Weight-Modellen",[7],"Brittany Lutz",{"type":9,"value":10,"toc":217},"minimark",[11,15,31,58,63,72,75,78,82,90,93,96,105,108,130,133,142,146,150,153,162,171,180,189,192,196,203],[12,13,14],"p",{},"Es gibt kein einzelnes bestes Modell für jede Softwareentwicklungsaufgabe. Eine neue Funktion implementieren, eine fehlgeschlagene Pipeline diagnostizieren und Sicherheitslücken beheben – all das stellt unterschiedliche Anforderungen an das jeweils zuständige Modell. GitLab Duo Agent Platform erweitert die Auswahl an GitLab-verwalteten Modellen um drei gehostete Open-Weight-Modelle: Kimi K3, GLM 5.3 und MiniMax M3.",[12,16,17,18,24,25,30],{},"Zusammen mit den bereits verfügbaren Frontier-Modellen in GitLab lässt sich jetzt genauer steuern, wie Qualität, Latenz und Kosten optimiert werden, abgestimmt auf die Anforderungen jedes einzelnen Workloads. Eine anspruchsvolle Aufgabe geht an Kimi K3 oder GLM 5.3, die in internen Tests vergleichbare Frontier-Modelle übertrafen und pro Aufruf weniger kosten, während sich Routinearbeit mit hohem Volumen an MiniMax M3 delegieren lässt. So oder so stehen bis zu 4-mal mehr Aufrufe pro ",[19,20,23],"a",{"href":21,"rel":22},"https://docs.gitlab.com/subscriptions/gitlab_credits/#models",[],"GitLab Credit"," zur Verfügung als bei manchen vergleichbaren Frontier-Modellen, mit mehr ",[19,26,29],{"href":27,"rel":28},"https://about.gitlab.com/de-de/blog/more-ai-models-for-duo-agent-platform-self-hosted/",[],"KI-Modelloptionen",", um Kosten an die Aufgabenkomplexität anzupassen.",[32,33,34,48,51],"blockquote",{},[12,35,36,43,44],{},[37,38],"img",{"src":39,"alt":40,"width":41,"style":42},"https://res.cloudinary.com/about-gitlab-com/image/upload/v1789485538/b1oin7kqcqoa4ezvabs0.png","",40,"vertical-align:middle;display:inline-block"," ",[45,46,47],"strong",{},"GitLab Transcend ist im Oktober zurück",[12,49,50],{},"Coding-Agenten beschleunigen die Entwicklung, doch Reviews, Sicherheitsrichtlinien und Release-Zyklen müssen mithalten können. Das Transcend-Event am 6. Oktober zeigt, wie GitLab Teams dabei hilft, diese Lücke zu schließen, und beleuchtet, was nötig ist, um das Tempo agentischer KI über den gesamten Software-Lebenszyklus hinweg mitzugehen.",[12,52,53],{},[19,54,57],{"href":55,"rel":56},"https://about.gitlab.com/de-de/events/transcend/virtual/",[],"Jetzt für den Livestream registrieren!",[59,60,62],"h2",{"id":61},"warum-ein-einziges-modell-lange-der-bequeme-ausweg-war","Warum ein einziges Modell lange der bequeme Ausweg war",[12,64,65,66,71],{},"Unterschiedliche Aufgaben in der ",[19,67,70],{"href":68,"rel":69},"https://about.gitlab.com/de-de/blog/gitlab-duo-agent-platform-is-generally-available/",[],"agentischen Entwicklung"," brauchen Unterschiedliches von einem KI-Modell. Ein lang laufendes Refactoring braucht ein großes Kontextfenster und tieferes Reasoning, während eine routinemäßige Aufgabe mit hohem Volumen oft besser von einem schnelleren, kosteneffizienteren Modell bedient wird. Wer für den einen Aufgabentyp optimiert, gibt beim anderen etwas auf.",[12,73,74],{},"Während Teams diesen technischen Kompromiss durchdenken, kommt als weitere Governance-Herausforderung hinzu, ob sich ein neues Modell überhaupt nutzen lässt. In regulierten Umgebungen müssen jedes Modell und die Infrastruktur, auf der es läuft, Sicherheits-, Compliance- und interne Prüfungen bestehen, bevor ein Team es einsetzen kann. Reviews und Freigaben dauern oft so lange, dass sich viele Teams auf ein einziges freigegebenes Modell festlegen, selbst wenn es nicht für jede Aufgabe die beste Wahl ist.",[12,76,77],{},"Die Kosten dieses Kompromisses summieren sich. Legt sich ein Team auf ein teureres Modell fest, um dessen schwierigste Aufgaben abzudecken, übernimmt dasselbe Modell am Ende auch Routinearbeit, die ein schnelleres, günstigeres Modell hätte erledigen können. Je mehr Agenten-Workloads wiederholte Modellaufrufe über lang laufende, mehrstufige Arbeit hinweg auslösen, desto stärker wächst die Lücke zwischen Kosten und Leistung.",[59,79,81],{"id":80},"der-kosten-leistungs-vorteil-von-open-weight-modellen","Der Kosten-Leistungs-Vorteil von Open-Weight-Modellen",[12,83,84,89],{},[19,85,88],{"href":86,"rel":87},"https://about.gitlab.com/de-de/blog/open-weight-model-letter/",[],"Open-Weight-Modelle"," machen die Modellwahl zu einem Hebel für die Balance zwischen Kosten und Leistung. Sie können die Inferenzkosten vieler agentischer Aufgaben potenziell senken, bei einer Leistung, die mit manchen Frontier-Modellen mithält.",[12,91,92],{},"Die neuen, in GitLab gehosteten Open-Weight-Modelle bieten deutlich mehr Aufrufe pro Credit als viele vergleichbare Frontier-Modelle, die bereits auf Duo Agent Platform verfügbar sind. 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Weitere Informationen zu Credit-Multiplikatoren und eine Aufschlüsselung des Credit-Verbrauchs pro Modell gibt es auf der ",[19,100,103],{"href":101,"rel":102},"https://docs.gitlab.com/subscriptions/gitlab_credits/#credit-multipliers",[],"Seite zu den GitLab Credits",".",[12,106,107],{},"Jedes der jetzt in GitLab Duo Agent Platform gehosteten Open-Weight-Modelle bringt eigene Stärken mit.",[109,110,111,118,124],"ul",{},[112,113,114,117],"li",{},[45,115,116],{},"Kimi K3 (Moonshot AI)"," ist das neueste Flaggschiffmodell des Unternehmens und gibt Teams Raum, um über große Codebasen oder lang laufende Agenten-Sessions hinweg zu arbeiten.",[112,119,120,123],{},[45,121,122],{},"GLM 5.3 (Z.ai)"," ist für Coding-Aufgaben mit langem Zeithorizont gebaut und gibt Teams ein Modell, das Kontext und Genauigkeit über ausgedehnte Agenten-Sessions hinweg hält.",[112,125,126,129],{},[45,127,128],{},"MiniMax M3 (MiniMax)"," ist darauf ausgelegt, die Rechenkosten bei lang laufender Arbeit niedrig zu halten, und auf hochvolumige, mehrstufige Agentenarbeit abgestimmt – eine starke Option, wenn Kosteneffizienz im großen Maßstab zählt.",[12,131,132],{},"Diese Demonstration zeigt die verfügbaren Open-Weight-Modelle:",[134,135],"iframe",{"src":136,"frameBorder":137,"allow":138,"referrerPolicy":139,"style":140,"title":141},"https://player.vimeo.com/video/1227818802?badge=0&autopause=0&player_id=0&app_id=58479","0","autoplay; fullscreen; picture-in-picture; clipboard-write; encrypted-media; web-share","strict-origin-when-cross-origin","position:absolute;top:0;left:0;width:100%;height:100%;","19.4 Open Weight Models V1",[143,144],"script",{"src":145},"https://player.vimeo.com/api/player.js",[59,147,149],{"id":148},"modellwahl-mit-eingebauter-kontrolle","Modellwahl mit eingebauter Kontrolle",[12,151,152],{},"Mit einer breiten Auswahl aus Open-Weight- und Frontier-Modellen von GitLab hat die eigene Duo-Agent-Platform-Implementierung jetzt mehr Freiheit, die Modellwahl für jede Aufgabe zu optimieren.",[12,154,155,156,161],{},"Die eigene Administration behält die zentrale Kontrolle darüber, welche Modelle Teams nutzen können, fest verankert in den eigenen Software-Entwicklungsworkflows. GitLab wählt zwar ",[19,157,160],{"href":158,"rel":159},"https://docs.gitlab.com/user/duo_agent_platform/model_selection/",[],"Standardmodelle"," auf Basis der Leistung aus, doch der Group Owner der eigenen Top-Level-Gruppe kann für jede Funktion ein anderes Standardmodell festlegen und kuratieren, aus welchen Modellen Teams wählen können – Einstellungen, die konsistent für jede untergeordnete Gruppe und jedes Projekt gelten.",[12,163,164,165,170],{},"Die Modellwahl lässt sich über GitLab-verwaltete, Self-Hosted- oder hybride KI-Deployment-Optionen an die eigenen Sicherheits-, Compliance- und Infrastrukturanforderungen anpassen. GitLab-verwaltete Modelle laufen vollständig innerhalb der Umgebung von GitLab, ohne dass eine eigene Infrastruktur aufgebaut oder gepflegt werden muss. ",[19,166,169],{"href":167,"rel":168},"https://about.gitlab.com/de-de/blog/agentic-ai-enterprise-control-self-hosted-duo-agent-platform-and-byom/",[],"Self-Hosted-Modelle"," laufen auf selbst verwalteter Infrastruktur, sodass der Modell-Traffic im eigenen Netzwerk bleibt. Hybride Deployments erlauben eine Mischung aus beidem: manche Modelle laufen über GitLab, andere auf der eigenen Infrastruktur, je nachdem, was der jeweilige Workload braucht.",[12,172,173,174,179],{},"Bevor ein ",[19,175,178],{"href":176,"rel":177},"https://handbook.gitlab.com/handbook/engineering/development/data-science/ai-powered/model-validation/model_evaluation/",[],"neues Modell"," in die Auswahl von GitLab Duo Agent Platform aufgenommen wird, prüfen wir es gegen interne Leistungs- und Qualitätsanforderungen. GitLab-verwaltete Modelle bringen ihre eigene, eingebaute Absicherung mit. Bevor GitLab einen Anbieter auswählt, um Modelle für Funktionen von Duo Agent Platform zu hosten, durchläuft dieser einen Prozess zum Risikomanagement bei Drittanbietern, um zu prüfen, ob er eine festgelegte Sicherheitsschwelle erreicht. Das umfasst eine Prüfung des Sicherheitsprogramms und der Kontrollen des Anbieters, etwa Zugriffsverwaltung, Daten-Governance und Risikomanagement-Praktiken, dazu Sicherheitsnachweise von Drittanbietern wie einen SOC-2-Type-2-Bericht oder eine aktive ISO-27001-Zertifizierung, sowie regelmäßige Penetrationstests mit risikobasierter Behebung von Schwachstellen.",[12,181,182,183,188],{},"Alle vier gehosteten Open-Weight-Modelle laufen über Fireworks AI, das diese Schwelle erreicht. Für Anfragen an GitLab Duo Agent Platform pflegt GitLab mit Fireworks eine ",[19,184,187],{"href":185,"rel":186},"https://docs.gitlab.com/user/gitlab_duo/data_usage/#data-retention",[],"Zero-Data-Retention-Richtlinie",": Eingabe- und Ausgabedaten der Modelle werden unmittelbar nach jeder Antwort gelöscht und nicht zur Missbrauchsüberwachung gespeichert.",[12,190,191],{},"Mit dieser Grundlage aus Governance und Sicherheit lassen sich Open-Weight-Modelle mit demselben Vertrauen in die eigenen Workflows einbinden, das auch für jedes GitLab-verwaltete Modell gilt.",[59,193,195],{"id":194},"jetzt-mit-open-weight-modellen-loslegen","Jetzt mit Open-Weight-Modellen loslegen",[12,197,198,199,104],{},"Kimi K3, GLM 5.3 und MiniMax M3 lassen sich jetzt als optionale Modelle in GitLab Duo Agent Platform auswählen, oder eines davon als Standardmodell für eine Funktion festlegen, sodass das eigene Team es automatisch nutzt. Für einen tieferen Einblick in die Modellunterstützung von Duo Agent Platform und Hinweise zur Modellwahl: ",[19,200,202],{"href":158,"rel":201},[],"die GitLab-KI-Modelldokumentation lesen",[12,204,205,206,211,212,104],{},"Neu bei Duo Agent Platform? ",[19,207,210],{"href":208,"rel":209},"https://about.gitlab.com/de-de/gitlab-duo-agent-platform/",[],"Kostenlose Testversion starten",". Bereits auf Premium oder Ultimate? ",[19,213,216],{"href":214,"rel":215},"https://docs.gitlab.com/user/duo_agent_platform/turn_on_off/",[],"Duo Agent Platform aktivieren",{"title":40,"searchDepth":218,"depth":218,"links":219},2,[220,221,222,223],{"id":61,"depth":218,"text":62},{"id":80,"depth":218,"text":81},{"id":148,"depth":218,"text":149},{"id":194,"depth":218,"text":195},"ai","2026-09-17","Vier Open-Weight-Modelle sind jetzt auf GitLab Duo Agent Platform verfügbar. 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