Gemini 2.5 Flash Image (Streaming)

Gemini 2.5 Flash Image (Streaming) is available through Starrise AI via the native Gemini API, supporting real-time SSE streaming of image generation results. Thinking chunks are pushed first, followed immediately by the final image chunk.

Key Capabilities

SSE streaming — Real-time delivery of thinking chunks and image chunks
Thinking mode — Internal reasoning chunks (thought: true) streamed before the image
Text-to-image — Generate images from text descriptions
Image editing — Pass a reference image via inline_data combined with text instructions
Aspect ratio control — 1:1, 4:3, 3:4, 16:9, 9:16
Resolution control — 1K (~1024px), 2K (~2048px), 4K (~4096px, by longest side)

SSE Response Format

The streaming endpoint returns newline-delimited SSE data lines, each starting with data: followed by a JSON object. There are three chunk types:

Thinking chunk — Arrives first; parts[0].thought is true
Image chunk — Contains parts[0].inlineData with mimeType and base64 data (note: camelCase in streaming responses)
Final usage chunk — Contains top-level usageMetadata with thoughtsTokenCount and per-modality token details

data: {"candidates":[{"content":{"role":"model","parts":[{"text":"...","thought":true}]}}],"usageMetadata":{"trafficType":"ON_DEMAND"},"modelVersion":"gemini-2.5-flash-image","createTime":"...","responseId":"..."}

data: {"candidates":[{"content":{"role":"model","parts":[{"inlineData":{"mimeType":"image/png","data":"<base64>"}}]}}],...}

data: {"usageMetadata":{"promptTokenCount":8,"candidatesTokenCount":1120,"totalTokenCount":1392,"trafficType":"ON_DEMAND","promptTokensDetails":[{"modality":"TEXT","tokenCount":8}],"candidatesTokensDetails":[{"modality":"IMAGE","tokenCount":1120}],"thoughtsTokenCount":264}}

In streaming responses, the image field is inlineData (camelCase), while in the request body it is inline_data (snake_case). This is native Gemini API behavior.

Text-to-Image Example

curl "https://ai.alad.com/v1beta/models/gemini-2.5-flash-image:streamGenerateContent?key=YOUR_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "contents": [
      {
        "role": "user",
        "parts": [
          { "text": "Generate an image of a mountain sunset" }
        ]
      }
    ],
    "generationConfig": {
      "responseModalities": ["TEXT", "IMAGE"],
      "imageConfig": {
        "aspectRatio": "16:9",
        "imageSize": "1K"
      }
    }
  }'

import requests, base64, json

url = "https://ai.alad.com/v1beta/models/gemini-2.5-flash-image:streamGenerateContent"
params = {"key": "YOUR_API_KEY"}
data = {
    "contents": [
        {
            "role": "user",
            "parts": [{"text": "Generate an image of a mountain sunset"}]
        }
    ],
    "generationConfig": {
        "responseModalities": ["TEXT", "IMAGE"],
        "imageConfig": {"aspectRatio": "16:9", "imageSize": "1K"}
    }
}

response = requests.post(url, params=params, json=data, stream=True)

for line in response.iter_lines():
    if not line:
        continue
    decoded = line.decode("utf-8")
    if not decoded.startswith("data:"):
        continue
    chunk = json.loads(decoded[len("data:"):].strip())

    candidates = chunk.get("candidates", [])
    if not candidates:
        continue
    parts = candidates[0].get("content", {}).get("parts", [])
    for part in parts:
        # Skip thinking chunks
        if part.get("thought"):
            continue
        # Save image chunk
        if "inlineData" in part:
            img_bytes = base64.b64decode(part["inlineData"]["data"])
            with open("output.png", "wb") as f:
                f.write(img_bytes)
            print("Image saved to output.png")

Image Editing Example (with Reference Image)

Pass both a text instruction and an inline_data reference image in the same parts array.

# First convert image to base64:
# BASE64=$(base64 -i your_photo.jpg)
#
# Then send the request:
curl "https://ai.alad.com/v1beta/models/gemini-2.5-flash-image:streamGenerateContent?key=YOUR_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "contents": [
      {
        "role": "user",
        "parts": [
          {
            "text": "This is a photo of me, please add an alpaca beside me"
          },
          {
            "inline_data": {
              "mime_type": "image/jpeg",
              "data": "<YOUR_BASE64_ENCODED_IMAGE>"
            }
          }
        ]
      }
    ],
    "generationConfig": {
      "responseModalities": ["TEXT", "IMAGE"],
      "imageConfig": {
        "aspectRatio": "1:1",
        "imageSize": "1K"
      }
    }
  }'

import requests, base64, json

# Read and encode the reference image
with open("your_photo.jpg", "rb") as f:
    image_b64 = base64.b64encode(f.read()).decode("utf-8")

url = "https://ai.alad.com/v1beta/models/gemini-2.5-flash-image:streamGenerateContent"
params = {"key": "YOUR_API_KEY"}
data = {
    "contents": [
        {
            "role": "user",
            "parts": [
                {
                    "text": "This is a photo of me, please add an alpaca beside me"
                },
                {
                    "inline_data": {
                        "mime_type": "image/jpeg",
                        "data": image_b64
                    }
                }
            ]
        }
    ],
    "generationConfig": {
        "responseModalities": ["TEXT", "IMAGE"],
        "imageConfig": {"aspectRatio": "1:1", "imageSize": "1K"}
    }
}

response = requests.post(url, params=params, json=data, stream=True)

for line in response.iter_lines():
    if not line:
        continue
    decoded = line.decode("utf-8")
    if not decoded.startswith("data:"):
        continue
    chunk = json.loads(decoded[len("data:"):].strip())

    candidates = chunk.get("candidates", [])
    if not candidates:
        continue
    parts = candidates[0].get("content", {}).get("parts", [])
    for part in parts:
        if part.get("thought"):
            continue
        if "inlineData" in part:
            img_bytes = base64.b64decode(part["inlineData"]["data"])
            with open("output.png", "wb") as f:
                f.write(img_bytes)
            print("Image saved to output.png")

Parameters

Parameter	Type	Required	Description
`key`	string	Yes	API key (query parameter)
`alt`	string	No	Set to `sse` to explicitly enable SSE mode (optional, streaming is the default behavior)
`contents[].parts[].text`	string	Yes	Text prompt or instruction
`contents[].parts[].inline_data.mime_type`	string	No	Reference image type: `image/jpeg`, `image/png`, `image/webp`
`contents[].parts[].inline_data.data`	string	No	Base64-encoded reference image data
`generationConfig.responseModalities`	array	Yes	`["IMAGE"]` or `["TEXT", "IMAGE"]`
`generationConfig.imageConfig.aspectRatio`	string	No	`1:1` / `4:3` / `3:4` / `16:9` / `9:16`
`generationConfig.imageConfig.imageSize`	string	No	`1K` / `2K` / `4K` (default `1K`)

API Reference

View the interactive API Playground for Gemini 2.5 Flash Image (Streaming).

Quick Start

Models

Resources

Gemini 2.5 Flash Image (Streaming)

Key Capabilities

SSE Response Format

Text-to-Image Example

Image Editing Example (with Reference Image)

Parameters

API Reference

​Key Capabilities

​SSE Response Format

​Text-to-Image Example

​Image Editing Example (with Reference Image)

​Parameters

API Reference

Key Capabilities

SSE Response Format

Text-to-Image Example

Image Editing Example (with Reference Image)

Parameters