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

Imagem para Imagem

Nano Banana 2 Reference-to-Image API by Google

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

Reference-to-image

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

Carregando configuração de parâmetros...

Saída

Inativo

As imagens geradas serão exibidas aqui

Configure os parâmetros e clique em executar para começar a gerar

Cada execução custará $0.08. Com $10 você pode executar aproximadamente 125 vezes.

Você pode continuar com:

Imagem para Vídeo Imagem para Imagem

Parâmetros

Exemplo 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",
    "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

Instale o pacote necessário para a sua linguagem de programação.

pip install requests

Autenticação

Todas as solicitações de API requerem autenticação por meio de uma chave de API. Você pode obter sua chave de API no painel do Atlas Cloud.

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

Cabeçalhos HTTP

import os

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

Mantenha sua chave de API segura

Nunca exponha sua chave de API em código do lado do cliente ou repositórios públicos. Use variáveis de ambiente ou um proxy de backend.

Enviar uma solicitação

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 uma solicitação

Envie uma solicitação de geração assíncrona. A API retorna um ID de predição que você pode usar para verificar o status e obter o resultado.

POST/api/v1/model/generateImage

Corpo da solicitação

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",
    "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']}")

Resposta

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

Verificar status

Consulte o endpoint de predição para verificar o status atual da sua solicitação.

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

Exemplo 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 status

processingA solicitação ainda está sendo processada.

completedA geração está completa. As saídas estão disponíveis.

succeededA geração foi bem-sucedida. As saídas estão disponíveis.

failedA geração falhou. Verifique o campo de erro.

Resposta concluída

{
  "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"
  }
}

Enviar arquivos

Envie arquivos para o armazenamento do Atlas Cloud e obtenha uma URL que pode ser usada nas suas solicitações de API. Use multipart/form-data para enviar.

POST/api/v1/model/uploadMedia

Exemplo de upload

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}")

Resposta

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

Schema de entrada

Os seguintes parâmetros são aceitos no corpo da solicitação.

Total: 0Obrigatório: 0Opcional: 0

Nenhum parâmetro disponível.

Exemplo de corpo da solicitação

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

Schema de saída

A API retorna uma resposta de predição com as URL de saída geradas.

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

Exemplo de resposta

{
  "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

O Atlas Cloud Skills integra mais de 300 modelos de IA diretamente no seu assistente de codificação com IA. Um comando para instalar e depois use linguagem natural para gerar imagens, vídeos e conversar com LLM.

Clientes compatíveis

Claude Code

OpenAI Codex

Gemini CLI

Cursor

Windsurf

VS Code

Trae

GitHub Copilot

Cline

Roo Code

Amp

Goose

Replit

40+ clientes compatíveis

Instalar

npx skills add AtlasCloudAI/atlas-cloud-skills

Configurar chave de API

Obtenha sua chave de API no painel do Atlas Cloud e defina-a como variável de ambiente.

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

Funcionalidades

Após a instalação, você pode usar linguagem natural no seu assistente de IA para acessar todos os modelos do Atlas Cloud.

Geração de imagensGere imagens com modelos como Nano Banana 2, Z-Image e mais.

Criação de vídeosCrie vídeos a partir de texto ou imagens com Kling, Vidu, Veo, etc.

Chat com LLMConverse com Qwen, DeepSeek e outros modelos de linguagem de grande escala.

Upload de mídiaEnvie arquivos locais para fluxos de trabalho de edição de imagens e imagem para vídeo.

Saiba mais

github.com/AtlasCloudAI/atlas-cloud-skills

MCP Server

O Atlas Cloud MCP Server conecta seu IDE com mais de 300 modelos de IA através do Model Context Protocol. Funciona com qualquer cliente compatível com MCP.

Clientes compatíveis

Cursor

VS Code

Windsurf

Claude Code

OpenAI Codex

Gemini CLI

Cline

Roo Code

100+ clientes compatíveis

Instalar

npx -y atlascloud-mcp

Configuração

Adicione a seguinte configuração ao arquivo de configuração de MCP do seu IDE.

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

Ferramentas disponíveis

atlas_generate_imageGere imagens a partir de prompts de texto.

atlas_generate_videoCrie vídeos a partir de texto ou imagens.

atlas_chatConverse com modelos de linguagem de grande escala.

atlas_list_modelsExplore mais de 300 modelos de IA disponíveis.

atlas_quick_generateCriação de conteúdo em uma etapa com seleção automática de modelo.

atlas_upload_mediaEnvie arquivos locais para fluxos de trabalho de API.

Saiba mais

github.com/AtlasCloudAI/mcp-server

API Schema

Schema não disponível

Sem exemplos disponíveis

Faça login para ver o histórico de solicitações

Você precisa fazer login para acessar o histórico de solicitações do modelo.

Fazer Login

Geração de imagens de nova geração

Saída em até 4K de resolução (níveis 512px / 1K / 2K / 4K)
10+ proporções de tela incluindo 21:9, 1:4, 8:1 e mais
Renderização de texto precisa e legível dentro das imagens
Qualidade quase Pro (~95%) na velocidade Flash

Edição inteligente e consistência

Consistência de personagens para até 5 personagens entre cenas
Fidelidade de objetos para até 14 objetos em um fluxo de trabalho
Edições direcionadas via linguagem natural (remover, substituir, reposar)
Mesclagem de múltiplas imagens e composição fluida

Novidades no Nano Banana 2

3-5x mais rápido que Pro

Construído sobre a arquitetura Gemini 3.1 Flash, o Nano Banana 2 gera imagens padrão em 4-8 segundos — comparado com 10-20 segundos do Nano Banana Pro.

Ancoragem por busca de imagens

O recurso destaque do NB2 — ele pode recuperar imagens de referência do mundo real via Google Search durante a geração, melhorando significativamente a precisão para pontos turísticos, pessoas famosas e logotipos de marcas.

Renderização de texto precisa

Gere texto preciso e legível para mockups de marketing, cartões comemorativos e conteúdo localizado. Você pode até traduzir e localizar o texto dentro de uma imagem.

Consistência multi-personagem

Mantenha a consistência visual para até 5 personagens e 14 objetos entre cenas — perfeito para storyboards, quadrinhos e campanhas 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 e quadrinhos

📸

Fotografia de produto

📊

Mockups de marketing

📱

Conteúdo para redes sociais

🔤

Design de sobreposição de texto

👤

Design de personagens

✨

Edição e retoque fotográfico

🎨

Conteúdo visual de marca

Por que escolher o Nano Banana 2?

⚡

Velocidade Flash

3-5x mais rápido que o Nano Banana Pro com tempo de geração padrão de 4-8 segundos

🎯

Qualidade quase Pro

Alcança aproximadamente 95% da qualidade de imagem do Pro na maioria dos cenários

💰

Custo-benefício

Aproximadamente metade do custo do Nano Banana Pro — tornando a geração de imagens IA de alta qualidade mais acessível

Especificações técnicas

Arquitetura:Gemini 3.1 Flash (GEMPIX2)

Suporte de resolução:De 512px a 4K (níveis 512px / 1K / 2K / 4K)

Proporções de tela:1:1, 4:3, 3:4, 2:3, 3:2, 16:9, 9:16, 1:4, 4:1, 8:1, 21:9

Consistência:Até 5 personagens + 14 objetos por fluxo de trabalho

Segurança de conteúdo:Marca d'água SynthID, compatível com o padrão C2PA

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

Experimente o Nano Banana 2

Geração de imagens de nível Pro na velocidade Flash — crie visuais impressionantes com consistência de personagens, renderização de texto e suporte a resolução 4K.

✨Créditos gratuitos para começar

⚡Acesso API instantâneo

🌐Sem configuração necessária

Google Nano Banana 2 Reference to Image

Nano Banana 2 Reference to Image (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 model is ideal for creating thumbnails, posters, promotional artwork, and scene summaries by leveraging the visual richness of existing video content alongside natural language guidance.

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.
Media resolution control — Balance detail and token usage for input video frames with LOW, MEDIUM, or HIGH media resolution modes.
Web & image search grounding — Optionally enable real-time web or image 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.
Format choice — Export in PNG or JPEG format.

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
output_format	No	Output format: png (default), jpeg

Advanced Options

Parameter	Required	Description
thinking_level	No	Reasoning depth: default, high, minimal. Higher levels improve quality on complex tasks but increase latency.
media_resolution	No	How input media frames are processed: default, low, medium, high. LOW reduces tokens per frame, allowing longer videos.
enable_web_search	No	If enabled, grounds generation with real-time web information.
enable_image_search	No	If enabled, grounds generation with real-time image search results.

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.
Choose output format — PNG for transparency support, JPEG for smaller file size.
Adjust advanced settings (optional) — set thinking level, media resolution, or enable 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, web search, and image 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
sku_image_search	Image 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)
     + (enable_image_search ? sku_image_search : 0)
     + (len(video_clips) > 0 ? sku_video_clip : 0)

Examples:

Resolution	Video Clip	Web Search	Image Search	Total Cost
1K	Yes	No	No	$0.08 +$ 0.07 = $0.15
2K	Yes	No	No	$0.12 +$ 0.07 = $0.19
4K	Yes	No	No	$0.16 +$ 0.07 = $0.23
1K	Yes	Yes	No	$0.08 +$ 0.07 + $0.014 = $ 0.164
1K	Yes	Yes	Yes	$0.08 +$ 0.07 + $0.014 +$ 0.014 = $0.178
1K	No	No	No	$0.08
2K	No	No	No	$0.12
4K	No	No	No	$0.16

The video clip fee ( $0.07), web search fee ($ 0.014), and image 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.
Set media_resolution: low when analyzing long videos to allow more frames within the context window.
2K offers excellent quality at a reasonable price — only $0.04 more than 1K per image.
YouTube URLs are supported directly — no need to download and re-upload public videos.

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.
If aspect_ratio is not selected, the model uses a default ratio.
4K resolution costs 2× the standard 1K rate.
Ensure your content and prompts comply with Google's Safety Guidelines.

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 Semelhantes

Nano Banana 2 Reference to Image Developer

NEW

Imagem para Imagem

DEV

Nano Banana 2 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.

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/imagem

Uma API para toda a IA de mídia.

Explorar Todos os Modelos

Nano Banana 2 Reference-to-Image API by Google

Entrada

Saída

Parâmetros

Exemplo de código

Instalar

Autenticação

Cabeçalhos HTTP

Enviar uma solicitação

Enviar uma solicitação

Corpo da solicitação

Resposta

Verificar status

Exemplo de polling

Valores de status

Resposta concluída

Enviar arquivos

Exemplo de upload

Resposta

Schema de entrada

Exemplo de corpo da solicitação

Schema de saída

Exemplo de resposta

Atlas Cloud Skills

Clientes compatíveis

Instalar

Configurar chave de API

Funcionalidades

MCP Server

Clientes compatíveis

Instalar

Configuração

Ferramentas disponíveis

API Schema

Faça login para ver o histórico de solicitações

Novidades no 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 que escolher o Nano Banana 2?

Velocidade Flash

Qualidade quase Pro

Custo-benefício

Especificações técnicas

Experimente o Nano Banana 2

Google Nano Banana 2 Reference to Image

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

Explorar Modelos Semelhantes

Nano Banana 2 Reference to Image Developer

Nano Banana 2 Text-to-Image

Nano Banana 2 Edit

Nano Banana Pro Text-to-image Ultra

Nano Banana Pro Edit Ultra

Nano Banana Pro Text-to-image

Nano Banana Pro Edit

Nano Banana Text-to-image

Nano Banana Edit

Imagen3

Image3 Fast

Imagen4 Fast