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Favicon für google

Google: Gemini 4 Carbon (batch)

google/gemini-4-carbon:batch

Vergleich

Gemini 4 Carbon is a frontier Gemini 4 model from Google for coding, agentic and complex reasoning work. It takes text, image, audio, video and file input, supports long decode of up to 1M output tokens through continuation, and controls thinking depth with low, medium and high reasoning effort.

Modalitäten
Eingabe- / Ausgabepreis
50 % Rabatt
1 $ / 5 $pro 1 Mio.
Kontext
1,0M
Veröffentlicht
10. Nov. 2026
Vergleich
AnbieterPreiseLeistungVerfügbarkeitAppsAktivitätFAQEntdecken

Anbieter

Verschiedene Unternehmen hosten dasselbe Modell. OpenRouter leitet Ihre Anfrage je nach gewähltem Routing-Modus an eines davon weiter — Balanced (Preis + Geschwindigkeit), Nitro (am schnellsten) oder Floor (am günstigsten).

Preise

Der durchschnittliche Preis, den Kunden tatsächlich für dieses Modell zahlen, neben den von Anbietern veröffentlichten Preisen. Durch Caching und Rabatte liegt der tatsächlich gezahlte Preis oft deutlich unter dem Listenpreis.

Leistung

Der Durchsatz gibt an, wie schnell das Modell schreibt (Token pro Sekunde – höher ist besser). Die Latenz ist die gesamte Umlaufzeit (niedriger ist besser). TTFT ist die Zeit bis zum ersten Token – also die Wartezeit, bis etwas angezeigt wird (niedriger ist besser).

Verfügbarkeit

Verfügbarkeit ist der prozentuale Anteil der letzten 3 Tage, in dem mindestens ein Anbieter auf Anfragen reagiert hat. Die Verfügbarkeit der Inferenz ist der prozentuale Anteil der Zeit, in der Inferenz erfolgreich bereitgestellt wurde. OpenRouter überwacht dies kontinuierlich und verwendet den nächstbesten Anbieter, wenn ein Anbieter einen Fehler zurückgibt.

Apps

Öffentliche Apps, die den meisten Datenverkehr an dieses Modell senden. Ein guter Anhaltspunkt dafür, wie echte Produktionsworkloads aussehen – und ein Hinweis darauf, für welche Anwendungsfälle dieses Modell am besten geeignet ist.

Aktivität

Token-Volumen und Anfrageaufkommen für dieses Modell im Zeitverlauf.

API

Direkt einsetzbarer Code zum Aufrufen dieses Modells. Die API von OpenRouter ist OpenAI-kompatibel – bei den meisten SDKs genügt es, die Basis-URL auszutauschen. Zwischen den Modellen ändert sich nur der unten stehende Modell-Slug.

Derzeit nicht über EU-regionales Routing verfügbar. Dokumentation zum regionsinternen Routing

Weitere Modelle entdecken

KI-Modelle mit Bildverarbeitung: Multimodale LLMs für das BildverständnisSammlungKI-ModellranglistenRangliste
50% off
2,00 $1,00 $10,00 $5,00 $0,10 $0,05 $0,10 $0,05 $----
--
AnbieterEingabe / Ausgabe /M
50% offDurchsatzVerfügbarkeit
  • Favicon für Google
    Eingabe 1,00 $ / Ausgabe 5,00 $
    50% off
    Durchsatz --Verfügbarkeit --

Noch nicht genügend Daten zur Verfügbarkeit für eine Anzeige vorhanden.

Wenn bei einem vorgelagerten Anbieter ein Fehler auftritt, können wir diesen durch die Weiterleitung an einen anderen funktionsfähigen Anbieter beheben, sofern Ihre Anfragefilter dies zulassen. Sie können programmgesteuert auf die Verfügbarkeitsdaten pro Anbieter zugreifen, und zwar über die Endpunkt-API. Erfahren Sie mehr über unsere Optionen für Lastverteilung und Anbieter-Routing.

Für Apps, die dieses Modell verwenden, liegen noch nicht genügend Daten vor.

Häufig gestellte Fragen

Gemini 4 Carbon is a frontier Gemini 4 model from Google for coding, agentic and complex reasoning work. It takes text, image, audio, video and file input, supports long decode of up to 1M output tokens through continuation, and controls thinking depth with low, medium and high reasoning effort.

Gemini 4 Carbon (batch) kostet 1,00 $/M Eingabe-Token und 5,00 $/M Ausgabe-Token, mit separaten Tarifen für Cache Read für 0,05 $/M tokens, Cache Write für 0,1875 $/M tokens, Image Input für 1,00 $/M tokens, Input Audio für 1,00 $/M tokens, Input Audio Cache für 0,05 $/M tokens und Web Search für 14,00 $/1K calls.

Gemini 4 Carbon (batch) hat ein Kontextfenster von 1.048.576 Token. Es unterstützt bis zu 1.048.576 Completion-Token.

Ja. Gemini 4 Carbon (batch) akzeptiert tools und tool_choice für Funktionsaufrufe. Es unterstützt auch strukturierte Ausgaben über ein JSON-Schema in response_format.

Gemini 4 Carbon (batch) akzeptiert Audio, Dateien wie PDFs, Bilder, Text und Video als Eingabe und gibt Text zurück.

Gemini Omni 1.2 Flash, Gemini Omni 1.1 Flash, Gemini 4 Argon und 29 weitere sind weitere Modelle von Google für die Modalität Text.

Gemini 4 Carbon (batch) wurde am 10. November 2026 veröffentlicht.

Weitere Modelle von Google

Gemini 4 Carbon

Gemini 4 Carbon is a frontier Gemini 4 model from Google for coding, agentic and complex reasoning work. It takes text, image, audio, video and file input, supports long decode of up to 1M output tokens through continuation, and controls thinking depth with low, medium and high reasoning effort.

Text1,0M Kontext2 $ / 10 $
Gemini 4 Carbon (batch)

Gemini 4 Carbon is a frontier Gemini 4 model from Google for coding, agentic and complex reasoning work. It takes text, image, audio, video and file input, supports long decode of up to 1M output tokens through continuation, and controls thinking depth with low, medium and high reasoning effort.

Text1,0M Kontext1 $ / 5 $
Gemini Omni 1.2 Flash

Gemini Omni 1.2 Flash is Google's native multimodal video generation and editing model, the successor to Gemini Omni 1.1 Flash. It generates clips up to 15 seconds long with native audio in 16:9 or 9:16, from 360p drafts up to 4K, and supports text-to-video, image-to-video, first and last frame interpolation, subject and video references with improved reference management, and editing or extending an uploaded video. Multi-turn editing and extension of a prior generation is supported through previous_job_id.

Note: video generation is only supported through the Video Generation API. See the guide: https://openrouter.ai/docs/guides/overview/multimodal/video-generation

Text131K Kontext1,50 $ / 9 $
Gemini Omni 1.1 Flash

Gemini Omni 1.1 Flash is Google's native multimodal video generation and editing model, the generally available successor to Gemini Omni Flash Preview. It is suited for text-to-video, image-to-video, first and last frame interpolation, subject and video references (up to three reference clips), and editing or extending an uploaded video, and generates clips from 360p drafts up to 4K with native audio in 16:9 or 9:16. Multi-turn editing and extension of a prior generation is supported through previous_job_id, up to 40 seconds of total video.

Note: video generation is only supported through the Video Generation API. See the guide: https://openrouter.ai/docs/guides/overview/multimodal/video-generation

Text131K Kontext1,50 $ / 9 $
Gemini 4 Argon

Gemini 4 Argon is Google's flagship reasoning model, built for complex software engineering, deep mathematical and scientific problem solving, and autonomous multi-step agents. Google trained it to keep context across long, multi-step tasks and to turn long documents mixing text, tables, charts and images into a single grounded output. It leads the Vals Index across finance, legal, coding and tax work, and supports long decode of up to 1M output tokens in a single response.

Text1,0M Kontext2 $ / 10 $
Gemini 4 Argon (batch)

Gemini 4 Argon is Google's flagship reasoning model, built for complex software engineering, deep mathematical and scientific problem solving, and autonomous multi-step agents. Google trained it to keep context across long, multi-step tasks and to turn long documents mixing text, tables, charts and images into a single grounded output. It leads the Vals Index across finance, legal, coding and tax work, and supports long decode of up to 1M output tokens in a single response.

Text1,0M Kontext1 $ / 5 $
Nano Banana 2.1

Nano Banana 2.1 (Gemini Nano Banana 2.1) is Google's image generation and editing model on the Flash tier, succeeding Nano Banana 2 and Nano Banana Pro. It improves product recontextualization, mask- and ink-based editing, and factual accuracy, and renders photorealistic skin tones, detailed materials, lighting, and coherent backgrounds. It accepts text and image inputs, returns images with optional text, and supports 1K, 2K, and 4K output plus extended aspect ratios via the image_config API Parameter.

Bild66K Kontext1,50 $ / 30 $
Gemini 3.5 Transcribe

Gemini 3.5 Transcribe is a speech-to-text model from Google. It is suited for synchronous transcription that needs word-level timestamps or speaker diarization, with support for up to eight speakers. Audio can be up to one hour, or 30 minutes when timestamps or diarization are enabled.

Transkription2 $ / 12 $
Gemini 3.8 Flash Lite TTS

Gemini 3.8 Flash Lite TTS is a text-to-speech model from Google and the fast, high-throughput member of the 3.8 TTS family alongside Gemini 3.8 Flash TTS. It is suited for conversational voice-agent pipelines, high-volume read-aloud, and voice replication workloads where latency and cost matter more than maximum expressiveness.

It accepts the same speech configuration as Gemini 3.1 Flash TTS Preview, including the 30 prebuilt studio voices, and supports Google's Voice Design and Voice Replication through voice_... identifiers.

Sprache0,50 $ / 6 $
Gemini 3.8 Flash TTS

Gemini 3.8 Flash TTS is a text-to-speech model from Google and the successor to Gemini 3.1 Flash TTS Preview. It is the creative tier of the 3.8 TTS family, suited for narration, character work, and multi-speaker dialogue where voice fidelity, acting nuance, and regional dialect coverage matter more than latency.

It accepts the same speech configuration as its predecessor, including the 30 prebuilt studio voices, and supports Google's Voice Design (custom voices from a text description) and Voice Replication (voices cloned from a short sample) through voice_... identifiers.

Sprache0,50 $ / 9 $
Gemini 3.8 Flash

Gemini 3.8 Flash is Google's most intelligent Flash model with significant gains from 3.7 Flash across software engineering, agentic tasks, and multi-step reasoning.

Text1,0M Kontext0,75 $ / 3,75 $
Gemini 3.8 Flash (batch)

Gemini 3.8 Flash is Google's most intelligent Flash model with significant gains from 3.7 Flash across software engineering, agentic tasks, and multi-step reasoning.

Text1,0M Kontext0,375 $ / 1,875 $
Gemini 3.7 Flash

Gemini 3.7 Flash is a multimodal model from Google for fast agentic workflows, coding, and complex multi-step reasoning. It is designed for tasks that require responsive performance and reliable multi-step problem solving.

Text1,0M Kontext0,75 $ / 3,75 $
Gemini 3.7 Flash (batch)

Gemini 3.7 Flash is a multimodal model from Google for fast agentic workflows, coding, and complex multi-step reasoning. It is designed for tasks that require responsive performance and reliable multi-step problem solving.

Text1,0M Kontext0,375 $ / 1,875 $
Gemini 3.6 Flash

Gemini 3.6 Flash is a high-efficiency model from Google for coding, agentic workflows, and web and app development. It is designed to produce polished outputs with fewer unnecessary edits and less hedging, while reducing token use and the number of model calls needed to complete a task.

Text1,0M Kontext0,75 $ / 3,75 $
Gemini 3.6 Flash (batch)

Gemini 3.6 Flash is a high-efficiency model from Google for coding, agentic workflows, and web and app development. It is designed to produce polished outputs with fewer unnecessary edits and less hedging, while reducing token use and the number of model calls needed to complete a task.

Text1,0M Kontext0,375 $ / 1,875 $
Gemini 3.5 Flash Lite

Gemini 3.5 Flash Lite is a high-efficiency model from Google with upgraded agentic capabilities. It is suited for subagents that execute focused tasks within complex, multi-agent workflows.

Text1,0M Kontext0,30 $ / 2,50 $
Gemini 3.5 Flash Lite (batch)

Gemini 3.5 Flash Lite is a high-efficiency model from Google with upgraded agentic capabilities. It is suited for subagents that execute focused tasks within complex, multi-agent workflows.

Text1,0M Kontext0,15 $ / 1,25 $
Nano Banana 2 Lite

Nano Banana 2 Lite (Gemini 3.1 Flash Lite Image) is Google's fastest, most cost-efficient Gemini image model, built for high-velocity developer pipelines and rapid-fire visual exploration. It delivers text-to-image generation in roughly 4 seconds — about 2.7× faster than Gemini 3.1 Flash Image — while keeping the character consistency, precise editing, and real-world knowledge of the Nano Banana family.

A single drop-in API handles text-to-image, image editing, and multi-image composition. As a multimodal model it also returns text alongside images. Outputs are generated at 1K resolution across 14 aspect ratios and carry an invisible SynthID watermark so they can be identified as AI-generated.

Positioned as the best balance of quality and speed in the Nano Banana 2 line, it lets you generate thousands of images at a fraction of the cost of heavier production models — ideal for prototyping, real-time apps, and visual workflows at scale.

Bild66K Kontext0,25 $ / 30 $
Nano Banana 2

Gemini 3.1 Flash Image, a.k.a. "Nano Banana 2," is Google’s latest state of the art image generation and editing model, delivering Pro-level visual quality at Flash speed. It combines advanced contextual understanding with fast, cost-efficient inference, making complex image generation and iterative edits significantly more accessible. Aspect ratios can be controlled with the image_config API Parameter

Bild131K Kontext0,50 $ / 60 $