Gemini 2.5 Flash Image Preview Edit | Fast Image Editing API

Gemini 2.5 Flash Image

Gemini 2.5 Flash Image is Google’s state-of-the-art image generation and editing model. It is a new variant of the Gemini 2.5 family, specifically designed for fast, conversational, and multi-turn creative workflows. This model is made available to developers through the Gemini API, Google AI Studio, and Vertex AI.

Key Features

Native Image Generation and Editing: Gemini 2.5 Flash Image is a multimodal model that natively understands and generates images. This allows for a seamless, unified workflow for creating and editing visuals.
Multi-image Fusion: This powerful feature allows you to combine multiple input images into a single, cohesive, new visual. For example, you can integrate a product into a new scene or restyle a room by merging images of different furniture and decor.
Character and Style Consistency: A significant advancement is the ability to maintain a consistent character, object, or style across multiple prompts and images. This is essential for storytelling, branding, and generating a series of cohesive assets without needing time-consuming fine-tuning.
Conversational Editing: The model enables precise, targeted edits using natural language. You can make specific changes like blurring a background, removing an object, altering a subject’s pose, or colorizing a black-and-white photo by simply describing the desired outcome.
Visual Reasoning: Gemini 2.5 Flash Image benefits from the Gemini model’s deep world knowledge. It can go beyond simple photorealism to perform complex tasks that require genuine understanding, such as interpreting hand-drawn diagrams, assisting with educational queries, and following multi-step instructions.
SynthID Watermarking: To promote responsible AI and transparency, all images created or edited with Gemini 2.5 Flash Image are embedded with an invisible digital watermark from SynthID. This watermark helps identify the content as AI-generated or edited.

Gemini 2.5 Flash Image Preview Edit API — Quick start

Grab a WaveSpeedAI API key, then call POST https://api.wavespeed.ai/api/v3/google/gemini-2.5-flash-image-preview/edit with your input as JSON. The endpoint returns a prediction id; poll the prediction endpoint until status flips to completed, then read the output URL from data.outputs[0]. Examples for Gemini 2.5 Flash Image Preview Edit below.

HTTP example

# Submit the prediction
curl -X POST "https://api.wavespeed.ai/api/v3/google/gemini-2.5-flash-image-preview/edit" \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer $WAVESPEED_API_KEY" \
  -d '{
    "prompt": "A cinematic shot of a city at sunset, soft golden light",
    "aspect_ratio": "1:1",
    "output_format": "png",
    "enable_sync_mode": false,
    "enable_base64_output": false
}'

# Response includes a prediction id. Poll for the result:
curl -X GET "https://api.wavespeed.ai/api/v3/predictions/{request_id}/result" \
  -H "Authorization: Bearer $WAVESPEED_API_KEY"

# When status is "completed", read the output from data.outputs[0].

Node.js example

// npm install wavespeed
const WaveSpeed = require('wavespeed');

const client = new WaveSpeed(); // reads WAVESPEED_API_KEY from env

const result = await client.run("google/gemini-2.5-flash-image-preview/edit", {
        "prompt": "A cinematic shot of a city at sunset, soft golden light",
        "aspect_ratio": "1:1",
        "output_format": "png",
        "enable_sync_mode": false,
        "enable_base64_output": false
});

console.log(result.outputs[0]); // → URL of the generated output

Python example

# pip install wavespeed
import wavespeed

output = wavespeed.run(
    "google/gemini-2.5-flash-image-preview/edit",
    {
    "prompt": "A cinematic shot of a city at sunset, soft golden light",
    "aspect_ratio": "1:1",
    "output_format": "png",
    "enable_sync_mode": false,
    "enable_base64_output": false
}
)

print(output["outputs"][0])  # → URL of the generated output

Gemini 2.5 Flash Image Preview Edit API — Frequently asked questions

What is the Gemini 2.5 Flash Image Preview Edit API?

Gemini 2.5 Flash Image Preview Edit is a Google model for image editing, exposed as a REST API on WaveSpeedAI. Google Gemini 2.5 Flash Image Preview is an image-to-image editing model with advanced creative controls for precise image edits. Ready-to-use REST inference API, best performance, no coldstarts, affordable pricing. You can call it programmatically or try it from the playground above.

How do I call the Gemini 2.5 Flash Image Preview Edit API?

POST your input parameters to the model's REST endpoint (shown in the API tab of this playground) with your WaveSpeedAI API key in the Authorization header. Submission returns a prediction ID; poll the prediction endpoint until status flips to "completed", then read the output URL from the result. The playground generates a ready-to-paste code sample in Python, JavaScript, or cURL for whatever inputs you've set. Full request/response shape is documented at https://wavespeed.ai/docs/docs-api/google/google-gemini-2.5-flash-image-preview-edit.

How much does Gemini 2.5 Flash Image Preview Edit cost per run?

Gemini 2.5 Flash Image Preview Edit starts at $0.038 per run. That figure is the base price — the final charge scales with the parameters you set in the form (output size, length, count, references, or whatever knobs this model exposes), so a higher-quality or larger output costs more than a minimal one. The exact cost for your current input is shown live next to the Generate button before you submit, and the actual per-call charge is recorded on the prediction afterwards.

What inputs does Gemini 2.5 Flash Image Preview Edit accept?

Key inputs: `prompt`, `images`, `aspect_ratio`, `enable_base64_output`, `enable_sync_mode`, `output_format`. The full JSON schema (types, defaults, allowed values) is rendered above the Generate button and mirrored in the API reference at https://wavespeed.ai/docs/docs-api/google/google-gemini-2.5-flash-image-preview-edit.

How long does Gemini 2.5 Flash Image Preview Edit take to generate?

Average end-to-end generation time on WaveSpeedAI is around 18 seconds per request — measured across recent runs. Queue time scales with global demand; live status is visible in the prediction record.

Can I use Gemini 2.5 Flash Image Preview Edit outputs commercially?

Commercial usage rights depend on the model's license, set by its provider (Google). The license summary appears on the model card above; see WaveSpeedAI's Terms of Service for platform-level conditions.

Related Models

README

Gemini 2.5 Flash Image

Key Features

Gemini 2.5 Flash Image Preview Edit API — Quick start

Gemini 2.5 Flash Image Preview Edit API — Frequently asked questions