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google/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.

TEXT-TO-IMAGENEW
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google/nano-banana-2/text-to-image
Nano Banana 2 Text-to-Image
文生图

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

输入

正在加载参数配置...

输出

空闲
生成的图片将在这里显示
配置参数后点击运行开始生成

每次运行将花费 0.08。$10 可运行约 125 次。

你可以继续：

图生视频图生图

参数

代码示例

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/text-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()

安装

安装所需的依赖包。

bash
pip install requests

认证

所有 API 请求需要通过 API Key 进行认证。您可以在 Atlas Cloud 控制台获取 API Key。

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

HTTP 请求头

python
import os

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

切勿在客户端代码或公开仓库中暴露您的 API Key。请使用环境变量或后端代理。

提交请求

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())

提交请求

提交一个异步生成请求。API 返回一个 prediction ID，您可以用它来检查状态和获取结果。

POST/api/v1/model/generateImage

请求体

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/text-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']}")

响应

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

检查状态

轮询 prediction 端点以检查请求的当前状态。

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

轮询示例

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)

状态值

processing请求仍在处理中。
completed生成完成，输出可用。
succeeded生成成功，输出可用。
failed生成失败，请检查 error 字段。

完成响应

{
  "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"
  }
}

上传文件

将文件上传到 Atlas Cloud 存储，获取可在 API 请求中使用的 URL。使用 multipart/form-data 上传。

POST/api/v1/model/uploadMedia

上传示例

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}")

响应

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

Input Schema

以下参数在请求体中被接受。

总计: 0必填: 0可选: 0

暂无可用参数。

请求体示例

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

Output Schema

API 返回包含生成输出 URL 的 prediction 响应。

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

响应示例

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 将 300+ AI 模型直接集成到您的 AI 编程助手中。一条命令安装，即可用自然语言生成图像、视频和与 LLM 对话。

支持的客户端

Claude Code
OpenAI Codex
Gemini CLI
Cursor
Windsurf
VS Code
Trae
GitHub Copilot
Cline
Roo Code
Amp
Goose
Replit
40+ 支持的客户端

安装

bash
npx skills add AtlasCloudAI/atlas-cloud-skills

设置 API Key

从 Atlas Cloud 控制台获取 API Key，并将其设置为环境变量。

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

功能

安装后，您可以在 AI 助手中使用自然语言访问所有 Atlas Cloud 模型。

图像生成使用 Nano Banana 2、Z-Image 等模型生成图像。
视频创作使用 Kling、Vidu、Veo 等模型从文本或图像创建视频。
LLM 对话与 Qwen、DeepSeek 等大语言模型对话。
媒体上传上传本地文件用于图像编辑和图生视频工作流。
了解更多

github.com/AtlasCloudAI/atlas-cloud-skills

MCP Server

Atlas Cloud MCP Server 通过 Model Context Protocol 将您的 IDE 与 300+ AI 模型连接。支持任何兼容 MCP 的客户端。

支持的客户端

Cursor
VS Code
Windsurf
Claude Code
OpenAI Codex
Gemini CLI
Cline
Roo Code
100+ 支持的客户端

安装

bash
npx -y atlascloud-mcp

配置

将以下配置添加到您的 IDE 的 MCP 设置文件中。

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

可用工具

atlas_generate_image从文本提示生成图像。
atlas_generate_video从文本或图像创建视频。
atlas_chat与大语言模型对话。
atlas_list_models浏览 300+ 可用 AI 模型。
atlas_quick_generate一步式内容创建，自动选择最佳模型。
atlas_upload_media上传本地文件用于 API 工作流。
了解更多

github.com/AtlasCloudAI/mcp-server

API Schema

Schema 不可用

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Nano Banana 2 — Pro 级质量，Flash 级速度

V2

又称 Gemini 3.1 Flash Image

Google DeepMind 最新图像模型，融合了 Nano Banana Pro 的高级能力与 Gemini Flash 的极速性能 — 生成速度快 3-5 倍，支持最高 4K 分辨率，单个工作流中可保持多达 5 个角色的一致性。

新一代图像生成
  • 最高 4K 分辨率输出（512px / 1K / 2K / 4K 四档）
  • 10+ 种宽高比，包括 21:9、1:4、8:1 等
  • 精准清晰的图中文字渲染
  • 接近 Pro 级画质（约 95%），Flash 级速度
智能编辑与一致性
  • 跨场景最多 5 个角色的一致性保持
  • 单个工作流中最多 14 个物体的保真度
  • 通过自然语言进行精准编辑（移除、替换、调姿）
  • 多图融合与无缝合成

Nano Banana 2 新特性

比 Pro 快 3-5 倍

基于 Gemini 3.1 Flash 架构，Nano Banana 2 标准图像生成仅需 4-8 秒，而 Nano Banana Pro 需要 10-20 秒。

图像搜索增强

NB2 的亮点功能 — 生成过程中可通过 Google 搜索检索真实世界参考图像，显著提升地标、名人和品牌标志的生成准确度。

精准文字渲染

为营销稿、贺卡和本地化内容生成准确清晰的文字，甚至可以在图像中直接翻译和本地化文字。

多角色一致性

跨场景保持最多 5 个角色和 14 个物体的视觉一致性 — 非常适合分镜、漫画创作和营销活动。

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

Nano Banana 2 is powered by Gemini 3.1 Flash Image — Google DeepMind

使用场景

🎬
分镜与漫画创作
📸
产品摄影
📊
营销设计稿
📱
社交媒体内容
🔤
文字叠加设计
👤
角色设计
✨
照片编辑与修图
🎨
品牌视觉内容

为什么选择 Nano Banana 2?

⚡

Flash 级速度

比 Nano Banana Pro 快 3-5 倍，标准生成时间仅 4-8 秒
🎯

接近 Pro 级画质

在大多数场景下可达到 Pro 约 95% 的画质水平
💰

更具性价比

成本约为 Nano Banana Pro 的一半 — 让高质量 AI 图像生成更加普惠

技术规格

架构:Gemini 3.1 Flash (GEMPIX2)
分辨率支持:512px 至 4K（512px / 1K / 2K / 4K 四档）
宽高比:1:1, 4:3, 3:4, 2:3, 3:2, 16:9, 9:16, 1:4, 4:1, 8:1, 21:9
一致性:单工作流最多 5 个角色 + 14 个物体
内容安全:SynthID 水印，兼容 C2PA 标准
API 访问:Gemini API、Vertex AI、AI Studio、Gemini CLI

立即体验 Nano Banana 2

Pro 级画质 Flash 级速度 — 轻松创建具有角色一致性、文字渲染和 4K 分辨率支持的精美视觉内容。

✨免费额度开始
⚡即时 API 访问
🌐无需任何设置

Google Nano Banana 2 Text-to-Image

Nano Banana 2 Text-to-Image (Gemini 3.1 Flash Image) is Google’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 — all within seconds.

Why Choose This?

  • Fast generation Optimized for speed while maintaining high visual quality.

  • 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.

  • Cinematic quality Excels at photorealistic scenes with atmospheric lighting and anamorphic lens effects.

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

  • Format choice Export in PNG or JPEG format.

Parameters

ParameterRequiredDescription
promptYesText description of the desired image
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. Write your prompt — describe the image in detail, including style, lighting, and composition.
  2. Choose aspect ratio (optional) — select a preset or leave empty for default.
  3. Select resolution — choose 1K, 2K, or 4K based on your needs.
  4. Choose output format — PNG for transparency support, JPEG for smaller file size.
  5. Use Prompt Enhancer (optional) — click to automatically refine your description.
  6. Run — submit and download your generated image.

Pricing

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

Best Use Cases

  • Cinematic Imagery — Generate atmospheric scenes with anamorphic lens effects and film-like quality.
  • Character Portraits — Create detailed character illustrations with specific attributes.
  • Social Media Content — Produce eye-catching visuals for various platforms with flexible aspect ratios.
  • Marketing & Ads — Generate professional images for campaigns and promotions.
  • Concept Art — Visualize creative ideas with photorealistic rendering.

Pro Tips

  • Use cinematic language like "anamorphic lens look," "neon signs reflected in puddles," or "rainy Tokyo street at night" for atmospheric results.
  • Be specific about character attributes (hair color, clothing, accessories) for consistent results.
  • Match aspect ratio to your target platform: 9:16 for Stories/Reels, 16:9 for banners, 1:1 for feeds.
  • Try the Prompt Enhancer to automatically improve your descriptions.
  • 2K offers the best value — same price as 1K with higher resolution.

Notes

  • Prompt is the only required field.
  • 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.

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