google/nano-banana/text-to-image-developer

Open and Advanced Large-Scale Image Generative Models.

TEXT-TO-IMAGENEW
Nano Banana Text-to-image Developer
text-to-image
DEV

Open and Advanced Large-Scale Image Generative Models.

INPUT

Loading parameter configuration...

OUTPUT

Idle
Your generated images will appear here
Configure your settings and click Run to get started

Your request will cost $0.023 per run. For $10 you can run this model approximately 434 times.

Here's what you can do next:

Parametri

Esempio di codice

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/text-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()

Installa

Installa il pacchetto richiesto per il tuo linguaggio.

bash
pip install requests

Autenticazione

Tutte le richieste API richiedono l'autenticazione tramite una chiave API. Puoi ottenere la tua chiave API dalla dashboard di Atlas Cloud.

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

Header HTTP

python
import os

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

Non esporre mai la tua chiave API nel codice lato client o nei repository pubblici. Utilizza invece variabili d'ambiente o un proxy backend.

Invia una richiesta

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())

Invia una richiesta

Invia una richiesta di generazione asincrona. L'API restituisce un ID di previsione che puoi usare per controllare lo stato e recuperare il risultato.

POST/api/v1/model/generateImage

Corpo della richiesta

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/text-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']}")

Risposta

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

Controlla lo stato

Interroga l'endpoint di previsione per verificare lo stato attuale della tua richiesta.

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

Esempio di 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)

Valori di stato

processingLa richiesta รจ ancora in fase di elaborazione.
completedLa generazione รจ completata. I risultati sono disponibili.
succeededLa generazione รจ riuscita. I risultati sono disponibili.
failedLa generazione รจ fallita. Controlla il campo errore.

Risposta completata

{
  "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"
  }
}

Carica file

Carica file nello storage Atlas Cloud e ottieni un URL utilizzabile nelle tue richieste API. Usa multipart/form-data per il caricamento.

POST/api/v1/model/uploadMedia

Esempio di caricamento

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}")

Risposta

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

Schema di input

I seguenti parametri sono accettati nel corpo della richiesta.

Totale: 0Obbligatorio: 0Opzionale: 0

Nessun parametro disponibile.

Esempio di corpo della richiesta

json
{
  "model": "google/nano-banana/text-to-image-developer"
}

Schema di output

L'API restituisce una risposta di previsione con gli URL degli output generati.

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

Esempio di risposta

json
{
  "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 oltre 300 modelli di IA direttamente nel tuo assistente di codifica IA. Un comando per installare, poi usa il linguaggio naturale per generare immagini, video e chattare con LLM.

Client supportati

Claude Code
OpenAI Codex
Gemini CLI
Cursor
Windsurf
VS Code
Trae
GitHub Copilot
Cline
Roo Code
Amp
Goose
Replit
40+ client supportati

Installa

bash
npx skills add AtlasCloudAI/atlas-cloud-skills

Configura chiave API

Ottieni la tua chiave API dalla dashboard di Atlas Cloud e impostala come variabile d'ambiente.

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

Funzionalitร 

Una volta installato, puoi usare il linguaggio naturale nel tuo assistente IA per accedere a tutti i modelli Atlas Cloud.

Generazione di immaginiGenera immagini con modelli come Nano Banana 2, Z-Image e altri.
Creazione di videoCrea video da testo o immagini con Kling, Vidu, Veo, ecc.
Chat LLMChatta con Qwen, DeepSeek e altri grandi modelli linguistici.
Caricamento mediaCarica file locali per la modifica di immagini e flussi di lavoro da immagine a video.

Server MCP

Il server MCP di Atlas Cloud collega il tuo IDE con oltre 300 modelli di IA tramite il Model Context Protocol. Funziona con qualsiasi client compatibile MCP.

Client supportati

Cursor
VS Code
Windsurf
Claude Code
OpenAI Codex
Gemini CLI
Cline
Roo Code
100+ client supportati

Installa

bash
npx -y atlascloud-mcp

Configurazione

Aggiungi la seguente configurazione al file delle impostazioni MCP del tuo IDE.

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

Strumenti disponibili

atlas_generate_imageGenera immagini da prompt testuali.
atlas_generate_videoCrea video da testo o immagini.
atlas_chatChatta con grandi modelli linguistici.
atlas_list_modelsEsplora oltre 300 modelli di IA disponibili.
atlas_quick_generateCreazione di contenuti in un solo passaggio con selezione automatica del modello.
atlas_upload_mediaCarica file locali per i flussi di lavoro API.

API Schema

Schema not available

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Seedance 1.5 Pro

GENERAZIONE AUDIO-VISIVA NATIVA

Suono e Visione, Tutto in Una Sola Ripresa

Il rivoluzionario modello di IA di ByteDance che genera audio e video perfettamente sincronizzati simultaneamente da un unico processo unificato. Sperimenta la vera generazione audio-visiva nativa con sincronizzazione labiale di precisione millimetrica in oltre 8 lingue.

Advanced Image Generation
  • Multi-image fusion technology
  • Character consistency across generations
  • Style-preserving transformations
  • High-resolution output up to 4K
Smart Editing Tools
  • Text-based intelligent editing
  • Object addition and removal
  • Background replacement
  • Style transfer and artistic effects

Prompt Examples & Templates

Explore curated prompt templates to unlock the full potential of Nano Banana AI. Click to copy any prompt and start creating immediately.

Photo to Character Figure
Transform to Figure

Photo to Character Figure

Transform any photo into a realistic character figure with packaging and display
Prompt

turn this photo into a character figure. Behind it, place a box with the character's image printed on it, and a computer showing the Blender modeling process on its screen. In front of the box, add a round plastic base with the character figure standing on it. set the scene indoors if possible

Anime to Cosplay
Anime to Real

Anime to Cosplay

Transform anime illustrations into realistic cosplay photography
Prompt

Generate a highly detailed photo of a girl cosplaying this illustration, at Comiket. Exactly replicate the same pose, body posture, hand gestures, facial expression, and camera framing as in the original illustration. Keep the same angle, perspective, and composition, without any deviation

Person to Action Figure
Photo to Action Figure

Person to Action Figure

Transform people from photos into collectible action figures with custom packaging
Prompt

Transform the 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. Visualize this in a highly realistic way with attention to fine details.

Person to Funko Pop Figure
Photo to Funko Pop

Person to Funko Pop Figure

Transform photos into Funko Pop style collectible figures with custom packaging
Prompt

Transform the person in the photo into the style of a Funko Pop figure packaging box, presented in an isometric perspective. Label the packaging with the title 'ZHOGUE'. Inside the box, showcase the figure based on the person in the photo, accompanied by their essential items (such as cosmetics, bags, or others). Next to the box, also display the actual figure itself outside of the packaging, rendered in a realistic and lifelike style.

Product Design to Photorealistic Render
Design to Reality

Product Design to Photorealistic Render

Transform product design sketches into photorealistic renders
Prompt

turn this illustration of a perfume into a realistic version, Frosted glass bottle with a marble cap

Transform to Q-Version Character
Face Reference Control

Transform to Q-Version Character

Create cartoon characters with face shape reference control
Prompt

Transform the person from image 1 into a Q-version character design based on the face shape from image 2

Building to 3D Architecture Model
Architecture to Model

Building to 3D Architecture Model

Convert architectural photos into detailed physical models
Prompt

convert this photo into a architecture model. Behind the model, there should be a cardboard box with an image of the architecture from the photo on it. There should also be a computer, with the content on the computer screen showing the Blender modeling process of the figurine. In front of the cardboard box, place a cardstock and put the architecture model from the photo I provided on it. I hope the PVC material can be clearly presented. It would be even better if the background is indoors.

Technical Highlights

Performance
Lightning-Fast Generation

Optimized for speed with generation times under 2 seconds for most tasks, making it perfect for real-time applications and rapid prototyping workflows.

Quality
Exceptional Output Quality

Leveraging Google's advanced AI architecture to produce highly detailed, photorealistic images with accurate lighting, textures, and compositions.

Innovation
Novel View Synthesis

Revolutionary 2D-to-3D conversion capabilities enabling creation of multiple viewpoints from a single image, opening new possibilities for content creation.

Perfetto Per

๐Ÿ“ธ
Product Photography
๐ŸŽจ
Digital Art Creation
โœจ
Photo Enhancement
๐Ÿ“Š
Marketing Visuals
๐Ÿ‘ค
Character Design
๐Ÿ‘”
Virtual Try-On
๐Ÿ“ฑ
Social Media
๐Ÿ”„
Photo Restoration

Why Choose Nano Banana?

๐Ÿš€
No Setup Required
Start creating immediately without complex configurations or installations
๐ŸŽฏ
Precision Control
Fine-tune every aspect of your creation with intuitive text commands
๐Ÿ”„
Consistent Results
Maintain character and style consistency across multiple generations

Specifiche Tecniche

Model Architecture:Google AI Studio Powered
Processing Speed:< 2 seconds average generation time
Resolution Support:Up to 4096x4096 pixels
Format Support:PNG, JPEG, WebP output formats
Multi-modal Input:Text, Image, and Combined prompts
API Integration:RESTful API with comprehensive documentation

Sperimenta la Generazione Audio-Visiva Nativa

Unisciti a cineasti, inserzionisti e creatori di tutto il mondo che stanno rivoluzionando la creazione di contenuti video con la tecnologia rivoluzionaria di Seedance 1.5 Pro.

โœจFree Credits to Start
โšกInstant Access
๐ŸŒWorks Everywhere

Google Nano Banana Text-to-Image

Nano Banana Text-to-Image is Googleโ€™s lightweight yet powerful AI image generation model, built for creators who need fast, high-quality visuals from simple text prompts. It transforms words into expressive, realistic images with remarkable clarity, composition, and style diversity โ€” all within seconds.

Difference to Nano Banana Text-to-Image: This model is cheaper and less stable than the version of Nano Banana Text-to-Image.

Try the New Version of Nano Banana!

๐ŸŒŸ Why it stands out

  • Instant Image Creation Generate beautiful, coherent visuals from just a short text prompt โ€” no design skills required.

  • Versatile Visual Styles Supports realistic, illustrative, anime, and painterly outputs, adapting naturally to your creative intent.

  • Accurate Text-to-Scene Understanding Accurately interprets subjects, backgrounds, and object relationships to create contextually correct compositions.

  • Fast & Efficient Optimized for quick turnaround and minimal compute cost, perfect for rapid prototyping and social content.

  • Clean, Balanced Lighting Produces visually appealing results without overexposure or unnatural shadows โ€” ideal for portraits, landscapes, and product imagery.

โš™๏ธ Capabilities

  • Input: text prompt

  • Output: high-quality image (JPEG/PNG/WEBP)

  • Supports multiple aspect ratios and output format

  • Compatible with descriptive prompts such as:

    • โ€œA golden retriever playing in a field of sunflowers at sunset.โ€
    • โ€œA futuristic city skyline with neon reflections on wet streets.โ€
    • โ€œAn elegant still-life photo of coffee and croissants by a window.โ€

๐Ÿ’ฐ Pricing

  • $0.019 per image
  • Commercial use allowed

๐Ÿ’ก Best Use Cases

  • Social Media & Marketing โ€” Create on-brand visuals instantly.
  • Concept Art & Storyboarding โ€” Generate design ideas and moodboards effortlessly.
  • E-commerce & Advertising โ€” Produce high-quality product images without photography.
  • Education & Presentation โ€” Visualize complex ideas or creative concepts easily.

๐Ÿ“ Notes

Please ensure your prompts comply with Googleโ€™s Safety Guidelines. If an error occurs, review your prompt for restricted content, adjust it, and try again.

Inizia con Oltre 300 Modelli,

Esplora tutti i modelli

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