google/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.

IMAGE-TO-IMAGENEW
Nano Banana 2 Edit
gambar-ke-gambar

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

INPUT

Memuat konfigurasi parameter...

OUTPUT

Menunggu
Gambar yang dihasilkan akan muncul di sini
Konfigurasikan pengaturan Anda dan klik Jalankan untuk memulai

Permintaan Anda akan dikenakan biaya 0.08 per eksekusi. Dengan $10 Anda dapat menjalankan model ini sekitar 125 kali.

Berikut yang dapat Anda lakukan selanjutnya:

Parameter

Contoh kode

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/edit",
    "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()

Instalasi

Instal paket yang diperlukan untuk bahasa pemrograman Anda.

bash
pip install requests

Autentikasi

Semua permintaan API memerlukan autentikasi melalui API key. Anda bisa mendapatkan API key dari dasbor Atlas Cloud.

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

HTTP Headers

python
import os

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

Jangan pernah mengekspos API key Anda di kode sisi klien atau repositori publik. Gunakan variabel lingkungan atau proxy backend sebagai gantinya.

Kirim permintaan

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())

Kirim Permintaan

Kirim permintaan pembuatan asinkron. API mengembalikan prediction ID yang dapat Anda gunakan untuk memeriksa status dan mengambil hasil.

POST/api/v1/model/generateImage

Isi Permintaan

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/edit",
    "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']}")

Respons

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

Periksa Status

Polling prediction endpoint untuk memeriksa status permintaan Anda saat ini.

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

Contoh 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)

Nilai Status

processingPermintaan masih diproses.
completedPembuatan selesai. Output tersedia.
succeededPembuatan berhasil. Output tersedia.
failedPembuatan gagal. Periksa field error.

Respons Selesai

{
  "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"
  }
}

Unggah File

Unggah file ke penyimpanan Atlas Cloud dan dapatkan URL yang dapat Anda gunakan dalam permintaan API Anda. Gunakan multipart/form-data untuk mengunggah.

POST/api/v1/model/uploadMedia

Contoh Unggah

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}")

Respons

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

Input Schema

Parameter berikut diterima di isi permintaan.

Total: 0Wajib: 0Opsional: 0

Tidak ada parameter yang tersedia.

Contoh Isi Permintaan

json
{
  "model": "google/nano-banana-2/edit"
}

Output Schema

API mengembalikan respons prediction dengan URL output yang dihasilkan.

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

Contoh Respons

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 mengintegrasikan 300+ model AI langsung ke asisten pengkodean AI Anda. Satu perintah untuk menginstal, lalu gunakan bahasa alami untuk menghasilkan gambar, video, dan mengobrol dengan LLM.

Klien yang Didukung

Claude Code
OpenAI Codex
Gemini CLI
Cursor
Windsurf
VS Code
Trae
GitHub Copilot
Cline
Roo Code
Amp
Goose
Replit
40+ klien yang didukung

Instalasi

bash
npx skills add AtlasCloudAI/atlas-cloud-skills

Atur API Key

Dapatkan API key dari dasbor Atlas Cloud dan atur sebagai variabel lingkungan.

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

Kemampuan

Setelah diinstal, Anda dapat menggunakan bahasa alami di asisten AI Anda untuk mengakses semua model Atlas Cloud.

Pembuatan GambarBuat gambar dengan model seperti Nano Banana 2, Z-Image, dan lainnya.
Pembuatan VideoBuat video dari teks atau gambar dengan Kling, Vidu, Veo, dll.
Obrolan LLMMengobrol dengan Qwen, DeepSeek, dan model bahasa besar lainnya.
Unggah MediaUnggah file lokal untuk pengeditan gambar dan alur kerja gambar-ke-video.

MCP Server

Atlas Cloud MCP Server menghubungkan IDE Anda dengan 300+ model AI melalui Model Context Protocol. Berfungsi dengan klien apa pun yang kompatibel dengan MCP.

Klien yang Didukung

Cursor
VS Code
Windsurf
Claude Code
OpenAI Codex
Gemini CLI
Cline
Roo Code
100+ klien yang didukung

Instalasi

bash
npx -y atlascloud-mcp

Konfigurasi

Tambahkan konfigurasi berikut ke file pengaturan MCP di IDE Anda.

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

Alat yang Tersedia

atlas_generate_imageBuat gambar dari prompt teks.
atlas_generate_videoBuat video dari teks atau gambar.
atlas_chatMengobrol dengan model bahasa besar.
atlas_list_modelsJelajahi 300+ model AI yang tersedia.
atlas_quick_generatePembuatan konten satu langkah dengan pemilihan model otomatis.
atlas_upload_mediaUnggah file lokal untuk alur kerja API.

Schema API

Schema tidak tersedia

Silakan masuk untuk melihat riwayat permintaan

Anda perlu masuk untuk mengakses riwayat permintaan model Anda.

Masuk

Nano Banana 2 — Kualitas Pro, Kecepatan Flash

V2

Juga dikenal sebagai Gemini 3.1 Flash Image

Model gambar terbaru dari Google DeepMind yang menggabungkan kemampuan canggih Nano Banana Pro dengan kecepatan Gemini Flash — menghasilkan gambar 3-5x lebih cepat, resolusi hingga 4K, dan konsistensi karakter hingga 5 karakter dalam satu alur kerja.

Generasi Gambar Generasi Berikutnya
  • Output resolusi hingga 4K (tingkat 512px / 1K / 2K / 4K)
  • 10+ rasio aspek termasuk 21:9, 1:4, 8:1 dan lainnya
  • Rendering teks yang akurat dan terbaca dalam gambar
  • Kualitas mendekati Pro (~95%) dengan kecepatan Flash
Pengeditan Cerdas & Konsistensi
  • Konsistensi karakter hingga 5 karakter lintas adegan
  • Ketepatan objek hingga 14 objek dalam satu alur kerja
  • Pengeditan terarah melalui bahasa alami (hapus, ganti, ubah pose)
  • Penggabungan multi-gambar dan komposisi mulus

Yang Baru di Nano Banana 2

3-5x Lebih Cepat dari Pro

Dibangun di atas arsitektur Gemini 3.1 Flash, Nano Banana 2 menghasilkan gambar standar dalam 4-8 detik — dibandingkan 10-20 detik untuk Nano Banana Pro.

Image Search Grounding

Fitur unggulan NB2 — dapat mengambil gambar referensi dunia nyata melalui Google Search selama proses generasi, meningkatkan akurasi secara signifikan untuk landmark, tokoh terkenal, dan logo merek.

Rendering Teks Akurat

Hasilkan teks yang akurat dan terbaca untuk mockup pemasaran, kartu ucapan, dan konten lokal. Anda bahkan dapat menerjemahkan dan melokalisasi teks di dalam gambar.

Konsistensi Multi-Karakter

Pertahankan konsistensi visual untuk hingga 5 karakter dan 14 objek lintas adegan — sempurna untuk storyboard, komik, dan kampanye pemasaran.

Prompt Examples & Templates

Explore curated prompt templates showcasing Nano Banana 2's key capabilities — text rendering, character consistency, search grounding, and 4K output.

Marketing Mockup with Text
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

Multi-Scene Character
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

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 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.

Real-World Reference Generation
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 Design Render
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

Artistic Style Transformation
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

Ultra High Resolution Scene
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

Kasus Penggunaan

🎬
Storyboard & Komik
📸
Fotografi Produk
📊
Mockup Pemasaran
📱
Konten Media Sosial
🔤
Desain Overlay Teks
👤
Desain Karakter
Pengeditan & Retouching Foto
🎨
Konten Visual Merek

Mengapa Memilih Nano Banana 2?

Kecepatan Flash

3-5x lebih cepat dari Nano Banana Pro dengan waktu generasi standar 4-8 detik
🎯

Kualitas Mendekati Pro

Mencapai sekitar 95% kualitas gambar Pro dalam sebagian besar skenario
💰

Hemat Biaya

Sekitar setengah biaya Nano Banana Pro — membuat generasi gambar AI berkualitas tinggi lebih terjangkau

Spesifikasi Teknis

Arsitektur:Gemini 3.1 Flash (GEMPIX2)
Dukungan Resolusi:512px hingga 4K (tingkat 512px / 1K / 2K / 4K)
Rasio Aspek:1:1, 4:3, 3:4, 2:3, 3:2, 16:9, 9:16, 1:4, 4:1, 8:1, 21:9
Konsistensi:Hingga 5 karakter + 14 objek per alur kerja
Keamanan Konten:Watermark SynthID, kompatibel standar C2PA
Akses API:Gemini API, Vertex AI, AI Studio, Gemini CLI

Rasakan Nano Banana 2

Generasi gambar level Pro dengan kecepatan Flash — buat visual menakjubkan dengan konsistensi karakter, rendering teks, dan dukungan resolusi 4K.

Kredit Gratis untuk Memulai
Akses API Instan
🌐Tanpa Perlu Pengaturan

Google Nano Banana 2 Edit

Nano Banana 2 Edit (Gemini 3.1 Flash Image) is Google’s advanced AI-powered image editing and generation model, designed to make visual transformation as intuitive as describing it in words. Built on Google’s cutting-edge computer vision and generative research, it combines precision, flexibility, and semantic awareness for professional-grade editing.

Why Choose This?

  • Natural language editing Modify images using simple text instructions — the model understands context and relationships.

  • Multi-image reference Upload up to 14 reference images for complex edits and compositions.

  • Multi-resolution support Output in 1K, 2K, or 4K resolution based on your needs.

  • 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.

  • Prompt Enhancer Built-in tool to automatically improve your edit descriptions.

  • Format choice Export in PNG or JPEG format.

Parameters

ParameterRequiredDescription
imagesYesReference images to edit (max: 14, click "+ Add Item" to add more)
promptYesText description of the desired edit
aspect_ratioNoAspect ratio: 1:1, 3:2, 2:3, 3:4, 4:3, 4:5, 5:4, 9:16, 16:9, 21:9
resolutionNoOutput resolution: 1k (default), 2k, 4k
output_formatNoOutput format: png (default), jpeg

How to Use

  1. Upload reference images — add the images you want to edit (up to 14 images).
  2. Write your prompt — describe the edit clearly (e.g., "Change the man to a woman").
  3. Choose aspect ratio (optional) — select a preset or leave empty for default.
  4. Select resolution — choose 1K, 2K, or 4K based on your needs.
  5. Choose output format — PNG for transparency support, JPEG for smaller file size.
  6. Use Prompt Enhancer (optional) — click to automatically refine your description.
  7. Run — submit and download your edited image.

Pricing

ResolutionCost
1k$0.08
2k$0.12
4k$0.16

Best Use Cases

  • Character Modification — Change attributes like gender, age, clothing, or appearance.
  • Object Replacement — Swap elements within images while preserving context.
  • Style Transfer — Apply different visual styles to existing images.
  • Text Editing — Modify on-image text while maintaining design consistency.
  • Scene Adjustment — Change backgrounds, lighting, or environmental elements.

Pro Tips

  • Use clear, specific edit instructions for best results (e.g., "Change the man to a woman" rather than "modify the person").
  • Start with fewer reference images (1–3) for simpler edits.
  • More reference images can help with complex compositions but may affect stability.
  • 2K offers the best value — same price as 1K with higher resolution.
  • Try the Prompt Enhancer to automatically improve your descriptions.

Notes

  • Both images and prompt are required fields.
  • Maximum reference images: 14 (recommended: fewer images for better stability).
  • If aspect_ratio is not selected, the model uses a default ratio.
  • 4K resolution costs 2× the standard rate.
  • Ensure your prompts comply with Google's Safety Guidelines.

Mulai dari 300+ Model,

Jelajahi semua model