google/nano-banana-2/reference-to-image-developer

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Nano Banana 2 Reference-to-Image Developer API by Google

google/nano-banana-2/reference-to-image-developer

Reference-to-image-developer

Google's advanced AI-powered video-to-image generation model, designed to generate high-quality static images from video clips combined with text instructions.

Entrada

Cargando configuración de parámetros...

Salida

Inactivo

Las imágenes generadas se mostrarán aquí

Configura los parámetros y haz clic en ejecutar para comenzar a generar

Cada ejecución costará $0.056. Con $10 puedes ejecutar aproximadamente 178 veces.

Puedes continuar con:

Imagen a Video Imagen a Imagen

Parámetros

Ejemplo de código
import requests
import time

# Step 1: Start image generation
generate_url = "https://api.atlascloud.ai/api/v1/model/generateImage"
headers = {
    "Content-Type": "application/json",
    "Authorization": "Bearer $ATLASCLOUD_API_KEY"
}
data = {
    "model": "google/nano-banana-2/reference-to-image-developer",
    "prompt": "A beautiful landscape with mountains and lake",
    "width": 512,
    "height": 512,
    "steps": 20,
    "guidance_scale": 7.5,
}

generate_response = requests.post(generate_url, headers=headers, json=data)
generate_result = generate_response.json()
prediction_id = generate_result["data"]["id"]

# Step 2: Poll for result
poll_url = f"https://api.atlascloud.ai/api/v1/model/prediction/{prediction_id}"

def check_status():
    while True:
        response = requests.get(poll_url, headers={"Authorization": "Bearer $ATLASCLOUD_API_KEY"})
        result = response.json()

        if result["data"]["status"] == "completed":
            print("Generated image:", result["data"]["outputs"][0])
            return result["data"]["outputs"][0]
        elif result["data"]["status"] == "failed":
            raise Exception(result["data"]["error"] or "Generation failed")
        else:
            # Still processing, wait 2 seconds
            time.sleep(2)

image_url = check_status()

Instalar

Instala el paquete necesario para tu lenguaje de programación.

pip install requests

Autenticación

Todas las solicitudes de API requieren autenticación mediante una clave de API. Puedes obtener tu clave de API desde el panel de Atlas Cloud.

export ATLASCLOUD_API_KEY="your-api-key-here"

Encabezados HTTP

import os

API_KEY = os.environ.get("ATLASCLOUD_API_KEY")
headers = {
    "Content-Type": "application/json",
    "Authorization": f"Bearer {API_KEY}"
}

Mantén tu clave de API segura

Nunca expongas tu clave de API en código del lado del cliente ni en repositorios públicos. Usa variables de entorno o un proxy de backend en su lugar.

Enviar una solicitud

import requests

url = "https://api.atlascloud.ai/api/v1/model/generateImage"
headers = {
    "Content-Type": "application/json",
    "Authorization": "Bearer $ATLASCLOUD_API_KEY"
}
data = {
    "model": "your-model",
    "prompt": "A beautiful landscape"
}

response = requests.post(url, headers=headers, json=data)
print(response.json())

Enviar una solicitud

Envía una solicitud de generación asíncrona. La API devuelve un ID de predicción que puedes usar para verificar el estado y obtener el resultado.

POST/api/v1/model/generateImage

Cuerpo de la solicitud

import requests

url = "https://api.atlascloud.ai/api/v1/model/generateImage"
headers = {
    "Content-Type": "application/json",
    "Authorization": "Bearer $ATLASCLOUD_API_KEY"
}

data = {
    "model": "google/nano-banana-2/reference-to-image-developer",
    "input": {
        "prompt": "A beautiful landscape with mountains and lake"
    }
}

response = requests.post(url, headers=headers, json=data)
result = response.json()

print(f"Prediction ID: {result['id']}")
print(f"Status: {result['status']}")

Respuesta

{
  "id": "pred_abc123",
  "status": "processing",
  "model": "model-name",
  "created_at": "2025-01-01T00:00:00Z"
}

Verificar estado

Consulta el endpoint de predicción para verificar el estado actual de tu solicitud.

GET/api/v1/model/prediction/{prediction_id}

Ejemplo de polling

import requests
import time

prediction_id = "pred_abc123"
url = f"https://api.atlascloud.ai/api/v1/model/prediction/{prediction_id}"
headers = { "Authorization": "Bearer $ATLASCLOUD_API_KEY" }

while True:
    response = requests.get(url, headers=headers)
    result = response.json()
    status = result["data"]["status"]
    print(f"Status: {status}")

    if status in ["completed", "succeeded"]:
        output_url = result["data"]["outputs"][0]
        print(f"Output URL: {output_url}")
        break
    elif status == "failed":
        print(f"Error: {result['data'].get('error', 'Unknown')}")
        break

    time.sleep(3)

Valores de estado

processingLa solicitud aún se está procesando.

completedLa generación está completa. Las salidas están disponibles.

succeededLa generación fue exitosa. Las salidas están disponibles.

failedLa generación falló. Verifica el campo de error.

Respuesta completada

{
  "data": {
    "id": "pred_abc123",
    "status": "completed",
    "outputs": [
      "https://storage.atlascloud.ai/outputs/result.png"
    ],
    "metrics": {
      "predict_time": 8.3
    },
    "created_at": "2025-01-01T00:00:00Z",
    "completed_at": "2025-01-01T00:00:10Z"
  }
}

Subir archivos

Sube archivos al almacenamiento de Atlas Cloud y obtén una URL que puedes usar en tus solicitudes de API. Usa multipart/form-data para subir.

POST/api/v1/model/uploadMedia

Ejemplo de carga

import requests

url = "https://api.atlascloud.ai/api/v1/model/uploadMedia"
headers = { "Authorization": "Bearer $ATLASCLOUD_API_KEY" }

with open("image.png", "rb") as f:
    files = {"file": ("image.png", f, "image/png")}
    response = requests.post(url, headers=headers, files=files)

result = response.json()
download_url = result["data"]["download_url"]
print(f"File URL: {download_url}")

Respuesta

{
  "data": {
    "download_url": "https://storage.atlascloud.ai/uploads/abc123/image.png",
    "file_name": "image.png",
    "content_type": "image/png",
    "size": 1024000
  }
}

Schema de entrada

Los siguientes parámetros se aceptan en el cuerpo de la solicitud.

Total: 0Obligatorio: 0Opcional: 0

No hay parámetros disponibles.

Ejemplo de cuerpo de solicitud

{
  "model": "google/nano-banana-2/reference-to-image-developer"
}

Schema de salida

La API devuelve una respuesta de predicción con las URL de salida generadas.

idstringrequired

Unique identifier for the prediction.

statusstringrequired

Current status of the prediction.

processingcompletedsucceededfailed

modelstringrequired

The model used for generation.

outputsarray[string]

Array of output URLs. Available when status is "completed".

errorstring

Error message if status is "failed".

metricsobject

Performance metrics.

predict_timenumber

Time taken for image generation in seconds.

created_atstringrequired

ISO 8601 timestamp when the prediction was created.

Format: date-time

completed_atstring

ISO 8601 timestamp when the prediction was completed.

Format: date-time

Ejemplo de respuesta

{
  "id": "pred_abc123",
  "status": "completed",
  "model": "model-name",
  "outputs": [
    "https://storage.atlascloud.ai/outputs/result.png"
  ],
  "metrics": {
    "predict_time": 8.3
  },
  "created_at": "2025-01-01T00:00:00Z",
  "completed_at": "2025-01-01T00:00:10Z"
}

Atlas Cloud Skills

Atlas Cloud Skills integra más de 300 modelos de IA directamente en tu asistente de codificación con IA. Un solo comando para instalar y luego usa lenguaje natural para generar imágenes, videos y chatear con LLM.

Clientes compatibles

Claude Code

OpenAI Codex

Gemini CLI

Cursor

Windsurf

VS Code

Trae

GitHub Copilot

Cline

Roo Code

Amp

Goose

Replit

40+ clientes compatibles

Instalar

npx skills add AtlasCloudAI/atlas-cloud-skills

Configurar clave de API

Obtén tu clave de API desde el panel de Atlas Cloud y configúrala como variable de entorno.

export ATLASCLOUD_API_KEY="your-api-key-here"

Funcionalidades

Una vez instalado, puedes usar lenguaje natural en tu asistente de IA para acceder a todos los modelos de Atlas Cloud.

Generación de imágenesGenera imágenes con modelos como Nano Banana 2, Z-Image y más.

Creación de videosCrea videos a partir de texto o imágenes con Kling, Vidu, Veo, etc.

Chat con LLMChatea con Qwen, DeepSeek y otros modelos de lenguaje de gran escala.

Carga de mediosSube archivos locales para flujos de trabajo de edición de imágenes e imagen a video.

Más información

github.com/AtlasCloudAI/atlas-cloud-skills

MCP Server

Atlas Cloud MCP Server conecta tu IDE con más de 300 modelos de IA a través del Model Context Protocol. Funciona con cualquier cliente compatible con MCP.

Clientes compatibles

Cursor

VS Code

Windsurf

Claude Code

OpenAI Codex

Gemini CLI

Cline

Roo Code

100+ clientes compatibles

Instalar

npx -y atlascloud-mcp

Configuración

Agrega la siguiente configuración al archivo de configuración de MCP de tu IDE.

{
  "mcpServers": {
    "atlascloud": {
      "command": "npx",
      "args": [
        "-y",
        "atlascloud-mcp"
      ],
      "env": {
        "ATLASCLOUD_API_KEY": "your-api-key-here"
      }
    }
  }
}

Herramientas disponibles

atlas_generate_imageGenera imágenes a partir de indicaciones de texto.

atlas_generate_videoCrea videos a partir de texto o imágenes.

atlas_chatChatea con modelos de lenguaje de gran escala.

atlas_list_modelsExplora más de 300 modelos de IA disponibles.

atlas_quick_generateCreación de contenido en un solo paso con selección automática de modelo.

atlas_upload_mediaSube archivos locales para flujos de trabajo de API.

Más información

github.com/AtlasCloudAI/mcp-server

API Schema

Schema no disponible

Sin ejemplos disponibles

Por favor inicia sesión para ver el historial de solicitudes

Necesitas iniciar sesión para acceder al historial de solicitudes del modelo.

Iniciar Sesión

Generación de imágenes de nueva generación

Salida de hasta 4K de resolución (niveles 512px / 1K / 2K / 4K)
10+ relaciones de aspecto incluyendo 21:9, 1:4, 8:1 y más
Renderizado de texto preciso y legible dentro de las imágenes
Calidad casi Pro (~95%) a velocidad Flash

Edición inteligente y consistencia

Consistencia de personajes para hasta 5 personajes entre escenas
Fidelidad de objetos para hasta 14 objetos en un flujo de trabajo
Ediciones dirigidas mediante lenguaje natural (eliminar, reemplazar, reposar)
Fusión de múltiples imágenes y composición fluida

Novedades en Nano Banana 2

3-5x más rápido que Pro

Construido sobre la arquitectura Gemini 3.1 Flash, Nano Banana 2 genera imágenes estándar en 4-8 segundos — en comparación con 10-20 segundos de Nano Banana Pro.

Anclaje por búsqueda de imágenes

La característica destacada de NB2 — puede recuperar imágenes de referencia del mundo real a través de Google Search durante la generación, mejorando significativamente la precisión para monumentos, personas famosas y logotipos de marcas.

Renderizado de texto preciso

Genera texto preciso y legible para maquetas de marketing, tarjetas de felicitación y contenido localizado. Incluso puedes traducir y localizar el texto dentro de una imagen.

Consistencia multi-personaje

Mantén la consistencia visual para hasta 5 personajes y 14 objetos entre escenas — perfecto para storyboards, cómics y campañas de marketing.

Text Rendering

Marketing Mockup with Text

Generate marketing visuals with accurate, legible text — one of NB2's standout improvements

Prompt

A minimalist coffee shop promotional poster with the text 'MORNING BREW — Fresh Roasted Daily' in elegant serif font, warm earth tones, steam rising from a ceramic cup, clean layout with plenty of whitespace

Character Consistency

Multi-Scene Character

Maintain character consistency across multiple scenes — supports up to 5 characters per workflow

Prompt

A young woman with short red hair and freckles, wearing a green jacket, standing in a rainy Tokyo street at night with neon reflections on wet pavement, cinematic lighting, photorealistic

Photo to Action Figure

Person to Action Figure

Transform people from photos into collectible action figures with custom packaging

Prompt

Transform the person in the photo into an action figure, styled after [CHARACTER_NAME] from [SOURCE / CONTEXT]. Next to the figure, display the accessories including [ITEM_1], [ITEM_2], and [ITEM_3]. On the top of the toy box, write "[BOX_LABEL_TOP]", and underneath it, "[BOX_LABEL_BOTTOM]". Place the box in a [BACKGROUND_SETTING] environment.

Search Grounding

Real-World Reference Generation

Leverage Image Search Grounding to generate accurate real-world subjects like landmarks and brands

Prompt

A photorealistic aerial view of the Eiffel Tower at golden hour, with the Seine River winding through Paris below, warm sunset light casting long shadows, high detail, 4K resolution

Product Photography

Product Design Render

Create professional product photography with precise control over lighting and composition

Prompt

A frosted glass perfume bottle with a marble cap on a white marble surface, soft studio lighting from the left, subtle reflections, minimalist luxury aesthetic, product photography style

Style Transfer

Artistic Style Transformation

Apply diverse artistic styles while maintaining subject integrity

Prompt

Transform this photo into Studio Ghibli animation style, keeping the same composition and subjects, lush watercolor backgrounds, soft diffused lighting, whimsical atmosphere

4K Output

Ultra High Resolution Scene

Generate detailed scenes at up to 4K resolution with rich textures

Prompt

A cozy Japanese ramen shop interior at night, steam rising from bowls, warm amber lighting, detailed wooden counter with various condiments, a chef working in the background, 4K, ultra detailed

Casos de uso

🎬

Storyboards y cómics

📸

Fotografía de producto

📊

Maquetas de marketing

📱

Contenido para redes sociales

🔤

Diseño de superposición de texto

👤

Diseño de personajes

✨

Edición y retoque fotográfico

🎨

Contenido visual de marca

¿Por qué elegir Nano Banana 2?

⚡

Velocidad Flash

3-5x más rápido que Nano Banana Pro con un tiempo de generación estándar de 4-8 segundos

🎯

Calidad casi Pro

Alcanza aproximadamente el 95% de la calidad de imagen de Pro en la mayoría de los escenarios

💰

Económico

Aproximadamente la mitad del costo de Nano Banana Pro — haciendo la generación de imágenes IA de alta calidad más accesible

Especificaciones técnicas

Arquitectura:Gemini 3.1 Flash (GEMPIX2)

Soporte de resolución:De 512px a 4K (niveles 512px / 1K / 2K / 4K)

Relaciones de aspecto:1:1, 4:3, 3:4, 2:3, 3:2, 16:9, 9:16, 1:4, 4:1, 8:1, 21:9

Consistencia:Hasta 5 personajes + 14 objetos por flujo de trabajo

Seguridad de contenido:Marca de agua SynthID, compatible con el estándar C2PA

Acceso API:Gemini API, Vertex AI, AI Studio, Gemini CLI

Experimenta Nano Banana 2

Generación de imágenes de nivel Pro a velocidad Flash — crea visuales impresionantes con consistencia de personajes, renderizado de texto y soporte de resolución 4K.

✨Créditos gratuitos para empezar

⚡Acceso API instantáneo

🌐Sin configuración necesaria

Google Nano Banana 2 Reference to Image Developer

Nano Banana 2 Reference to Image Developer (Gemini 3.1 Flash Image) is Google's advanced AI-powered video-to-image generation model, designed to generate high-quality static images from video clips combined with text instructions. Built on the same cutting-edge model as Nano Banana 2 Edit, it adds the ability to use video content as a rich reference source — extracting visual context, themes, and key frames to synthesize new images with precision and semantic awareness.

This is the developer-tier variant of Nano Banana 2 Reference to Image, offering a streamlined parameter set. It is ideal for API integrations and workflows where output format flexibility and per-frame media resolution control are not required.

Why Choose This?

Video as reference — Provide a video clip (HTTP URL or YouTube URL) and let the model extract its visual context to guide image generation.
Multi-image reference — Optionally upload up to 10 additional reference images to complement the video input for complex compositions.
Natural language control — Describe exactly what you want with a text prompt; the model understands context, themes, and relationships from both the video and text.
Thinking levels — Choose how much internal reasoning the model applies — higher thinking levels improve quality on complex tasks.
Web search grounding — Optionally enable real-time web search to enrich generation with current information.
Multi-resolution output — Generate at 1K, 2K, or 4K resolution.
Flexible aspect ratios — Multiple options including 1:1, 3:2, 2:3, 3:4, 4:3, 4:5, 5:4, 9:16, 16:9, and 21:9.

How It Works

The model analyzes your video clip by sampling frames at the specified FPS rate, then interprets the visual content within its multimodal context window. Combined with your text prompt and any additional reference images, it synthesizes a new image grounded in the video's themes, style, and key visual elements. This makes it especially powerful for creating content that is visually consistent with existing video assets.

Parameters

Core Inputs

Parameter	Required	Description
prompt	Yes	Text description of the desired output image
video_clips	Yes	Source video clip(s) for reference generation (max: 1, see below)
images	No	Additional reference images (max: 10, click "+ Add Item" to add more)

Video Clip Fields

Field	Required	Description
url	Yes	URL of the source video clip. Supports HTTP URL or YouTube video URL. HTTP video is limited to 15MB.
start	Yes	Start time in seconds for trimming the video clip (min: 0)
ends	Yes	End time in seconds for trimming the video clip. Set 0 to use the whole video.
fps	Yes	Frame sampling rate (FPS) of the video clip. Range: 0–24. Lower values reduce token usage.

Output Options

Parameter	Required	Description
aspect_ratio	No	Aspect ratio: 1:1, 3:2, 2:3, 3:4, 4:3, 4:5, 5:4, 9:16, 16:9, 21:9
resolution	No	Output resolution: 1k (default), 2k, 4k

Advanced Options

Parameter	Required	Description
thinking_level	No	Reasoning depth: default, high, minimal. Higher levels improve quality on complex tasks but increase latency.
enable_web_search	No	If enabled, grounds generation with real-time web information.

How to Use

Provide a video clip — enter the video URL (HTTP or YouTube) and set start/end times and FPS sampling rate.
Write your prompt — describe the output image clearly (e.g., "Create a cinematic poster based on the key scenes in this video").
Add reference images (optional) — upload additional images to guide composition or style.
Choose aspect ratio (optional) — select a preset or leave empty for default.
Select resolution — choose 1K, 2K, or 4K based on your quality needs.
Adjust advanced settings (optional) — set thinking level or enable web search grounding.
Run — submit and download your generated image.

Pricing

The total cost is determined by the output image resolution multiplied by the number of output images, plus optional per-request fees for video clip input and web search grounding.

SKU Prices

SKU	Description	Unit Price
sku_1k	1K resolution output image	$0.08
sku_2k	2K resolution output image	$0.12
sku_4k	4K resolution output image	$0.16
sku_video_clip	Video clip input (per request)	$0.07
sku_web_search	Web search grounding (per request)	$0.014

Pricing Formula

cost = (resolution == "2k" ? sku_2k : (resolution == "4k" ? sku_4k : sku_1k)) * images
     + (enable_web_search ? sku_web_search : 0)
     + (len(video_clips) > 0 ? sku_video_clip : 0)

Examples:

Resolution	Video Clip	Web Search	Total Cost
1K	Yes	No	$0.08 +$ 0.07 = $0.15
2K	Yes	No	$0.12 +$ 0.07 = $0.19
4K	Yes	No	$0.16 +$ 0.07 = $0.23
1K	Yes	Yes	$0.08 +$ 0.07 + $0.014 = $ 0.164
1K	No	No	$0.08
2K	No	No	$0.12
4K	No	No	$0.16

The video clip fee ( $0.07) and web search fee ($ 0.014) are each charged once per request when the respective feature is enabled, regardless of content volume.

Best Use Cases

Video Thumbnail Generation — Automatically create compelling thumbnails that reflect the video's content and mood.
Promotional Posters — Generate movie-style or campaign posters grounded in actual video footage.
Scene Summarization Art — Create visual summaries or highlight artwork from long-form video content.
Brand Content Creation — Produce consistent image assets from brand video campaigns.
Educational Infographics — Transform instructional videos into static visual materials.
Social Media Assets — Generate platform-optimized images (vertical, square, landscape) from video content.

Pro Tips

Use low FPS (0.5–1) for long videos to keep token usage within limits while still capturing key frames.
Set precise start/end times to focus the model on the most relevant segment of your video.
Combine specific text prompts with the video input — vague prompts may produce generic results.
Add reference images alongside the video to guide composition style more precisely.
Use thinking_level: high for complex scene interpretations or when visual fidelity matters most.
YouTube URLs are supported directly — no need to download and re-upload public videos.
2K offers excellent quality at a reasonable price — only $0.04 more than 1K per image.
If you need output_format (PNG/JPEG) or media_resolution control, use the standard Reference to Image model instead.

Notes

Both prompt and video_clips are required fields.
Maximum video clips: 1 per request.
HTTP video URLs are limited to 15MB; use YouTube URLs for larger videos.
Maximum additional reference images: 10.
FPS range: 0–24. Higher FPS captures more frames but consumes more tokens.
The video clip fee ($0.07) is a flat per-request charge, not per frame or per second.
Output format is not configurable in this variant; use the standard model if PNG/JPEG selection is required.
Ensure your content and prompts comply with Google's Safety Guidelines.

Nano Banana 2 Reference to Image — Full-featured variant with output_format, media_resolution, and enable_image_search support.
Nano Banana 2 Edit — Edit images using text prompts and reference images (no video input).
Nano Banana 2 Text-to-Image — Generate images from text prompts only.
Nano Banana Pro Edit — Pro tier editing with enhanced quality.
Nano Banana Pro Text-to-Image — Pro tier image generation.

Explorar Modelos Similares

NEW

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Nano Banana 2 Text-to-Image

Google's lightweight yet powerful AI image generation model, built for creators who need fast, high-quality visuals from simple text prompts.

Nano Banana 2 Edit

Google's advanced AI-powered image editing and generation model, designed to make visual transformation as intuitive as describing it in words.

Nano Banana Pro Text-to-image Ultra

Nano Banana Pro is the next-generation Nano Banana image model, delivering sharper detail, richer color control, and faster diffusion for production-ready visuals.

Nano Banana Pro Edit Ultra

Nano Banana Pro Edit is an image editing tool built on the Nano Banana model family, designed for precise, AI-powered visual adjustments.

Nano Banana Pro Text-to-image

Nano Banana Pro is the next-generation Nano Banana image model, delivering sharper detail, richer color control, and faster diffusion for production-ready visuals.

Nano Banana Pro Edit

Nano Banana Pro Edit is an image editing tool built on the Nano Banana model family, designed for precise, AI-powered visual adjustments.

Nano Banana Text-to-image

Google's state-of-the-art image generation and editing model.

Nano Banana Edit

Google's state-of-the-art image generation and editing model.

Imagen3

Google's highest quality text-to-image model, capable of generating images with detail, rich lighting and beauty.

Image3 Fast

Google's highest quality text-to-image model, capable of generating images with detail, rich lighting and beauty.

Imagen4 Fast

Google's Imagen 4 flagship model.

Imagen4 Ultra

Google’s highest quality image generation model.

Imagen4

Google's Imagen 4 flagship model.

Openai GPT Image 2 Text-to-Image

GPT Image 2 text to image is OpenAI's fast, cost-efficient text-to-image generator powered by GPT-5 guidance. Create photorealistic shots, product renders, concept art, and stylized graphics from natural-language prompts (optionally conditioned with an image). Supports custom aspect ratios, seeds, negative prompts, hex color hints, and style presets. Ready-to-use REST inference API, best performance, no coldstarts, affordable pricing.

Openai GPT Image 2 Edit

GPT Image 2 Edit is OpenAI's image model for precise, natural-language edits. Add/remove objects, swap backgrounds, retouch faces, adjust colors/lighting, edit text/graphics, crop/resize, and apply hex color control. Ready-to-use REST inference API, best performance, no coldstarts, affordable pricing.

From

$0.01/imagen

Una sola API para toda la IA multimedia.

Explorar Todos los Modelos

Nano Banana 2 Reference-to-Image Developer API by Google

Entrada

Salida

Parámetros

Ejemplo de código

Instalar

Autenticación

Encabezados HTTP

Enviar una solicitud

Enviar una solicitud

Cuerpo de la solicitud

Respuesta

Verificar estado

Ejemplo de polling

Valores de estado

Respuesta completada

Subir archivos

Ejemplo de carga

Respuesta

Schema de entrada

Ejemplo de cuerpo de solicitud

Schema de salida

Ejemplo de respuesta

Atlas Cloud Skills

Clientes compatibles

Instalar

Configurar clave de API

Funcionalidades

MCP Server

Clientes compatibles

Instalar

Configuración

Herramientas disponibles

API Schema

Por favor inicia sesión para ver el historial de solicitudes

Novedades en Nano Banana 2

Prompt Examples & Templates

Marketing Mockup with Text

Multi-Scene Character

Person to Action Figure

Real-World Reference Generation

Product Design Render

Artistic Style Transformation

Ultra High Resolution Scene

Casos de uso

¿Por qué elegir Nano Banana 2?

Velocidad Flash

Calidad casi Pro

Económico

Especificaciones técnicas

Experimenta Nano Banana 2

Google Nano Banana 2 Reference to Image Developer

Why Choose This?

How It Works

Parameters

Core Inputs

Video Clip Fields

Output Options

Advanced Options

How to Use

Pricing

SKU Prices

Pricing Formula

Best Use Cases

Pro Tips

Notes

Related Models

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