# How to use gemini-2.5-flash-image with Google AI Studio

Here’s the fastest way to get started with **gemini-2.5-flash-image** (Google’s native text-to-image & image-editing model).

### 1) Pick your access path

* **Gemini API (AI Studio)** — simplest way; auth via API key. Great for apps, servers, and quick prototyping. ([Google AI for Developers](https://ai.google.dev/gemini-api/docs?utm_source=chatgpt.com))
    
* **Vertex AI** — GCP-managed, quotas/billing/enterprise controls; same model name. Note: preview image models are being retired; migrate to `gemini-2.5-flash-image`. ([Google Cloud](https://cloud.google.com/vertex-ai/generative-ai/docs/multimodal/image-generation?utm_source=chatgpt.com))
    

---

### 2) Get an API key (AI Studio)

Create a key in **Google AI Studio** → “Get API key,” then set `GEMINI_API_KEY` in your environment. Docs + model card: ([Google AI for Developers](https://ai.google.dev/gemini-api/docs?utm_source=chatgpt.com))

---

### 3) Minimal “text → image” call

**cURL (Gemini API)**

```bash
curl -s -X POST \
  "https://generativelanguage.googleapis.com/v1beta/models/gemini-2.5-flash-image:generateContent" \
  -H "x-goog-api-key: $GEMINI_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "contents":[{"parts":[{"text":
      "A cozy, cinematic coffee shop interior at golden hour, shallow depth of field, 35mm, soft rim light"}
    ]}]
  }'
```

The response includes an image as base64 in `candidates[0].content.parts[].inlineData.data`. ([Google AI for Developers](https://ai.google.dev/gemini-api/docs/image-generation))

**JavaScript (Node)**

```js
import { GoogleGenerativeAI } from "@google/generative-ai";
import fs from "fs";

const ai = new GoogleGenerativeAI(process.env.GEMINI_API_KEY);
const prompt = "Minimalist poster of a red fox in the snow, high contrast, grainy film look";

const res = await ai.models.generateContent({
  model: "gemini-2.5-flash-image",
  contents: prompt,
});
for (const part of res.candidates[0].content.parts) {
  if (part.inlineData) {
    fs.writeFileSync("output.png", Buffer.from(part.inlineData.data, "base64"));
  }
}
```

([Google AI for Developers](https://ai.google.dev/gemini-api/docs/image-generation))

**Python**

```python
from google import genai
from google.genai import types
from io import BytesIO
from PIL import Image

client = genai.Client()  # reads GOOGLE_API_KEY or similar env var
prompt = "Architectural render of a tranquil Japanese courtyard, dusk, volumetric light"

resp = client.models.generate_content(
    model="gemini-2.5-flash-image",
    contents=prompt,
)
image_bytes = next(
    (p.inline_data.data for p in resp.candidates[0].content.parts if getattr(p, "inline_data", None)),
    None,
)
if image_bytes:
    img = Image.open(BytesIO(image_bytes))
    img.save("courtyard.png")
```

([Google AI for Developers](https://ai.google.dev/gemini-api/docs/image-generation))

---

### 4) Control output (aspect ratio, image-only, etc.)

Add a config to your call:

**JS (force image-only + 16:9)**

```js
const res = await ai.models.generateContent({
  model: "gemini-2.5-flash-image",
  contents: "Wide cinematic landscape of Icelandic black sand beach, long exposure",
  config: {
    responseModalities: ["Image"],
    imageConfig: { aspectRatio: "16:9" }
  }
});
```

(Also available in Python/Go.) ([Google AI for Developers](https://ai.google.dev/gemini-api/docs/image-generation))

---

### 5) Image editing / multi-image fusion

Pass input images (base64) alongside your text instruction.

**cURL (edit an image)**

```bash
IMG_BASE64=$(base64 -w0 input.jpg)
curl -s -X POST \
  "https://generativelanguage.googleapis.com/v1beta/models/gemini-2.5-flash-image:generateContent" \
  -H "x-goog-api-key: $GEMINI_API_KEY" -H 'Content-Type: application/json' \
  -d "{
    \"contents\": [{
      \"parts\": [
        {\"text\": \"Replace the sky with dramatic storm clouds; keep colors natural\"},
        {\"inline_data\": {\"mime_type\":\"image/jpeg\",\"data\":\"$IMG_BASE64\"}}
      ]
    }]
  }"
```

You can include multiple `inline_data` parts to **merge** images (e.g., place a product into a new scene). ([Google AI for Developers](https://ai.google.dev/gemini-api/docs/image-generation))

---

### 6) Prompting tips (huge quality boost)

Describe a full **scene** (camera, lens, lighting, mood, materials). Narrative prompts reliably beat keyword lists. The official guide includes templates for photorealistic, logo, sticker, and negative-space compositions. ([Google AI for Developers](https://ai.google.dev/gemini-api/docs/image-generation))

---

### 7) Pricing, safety & watermarks

* **Pricing (Gemini API):** blog post lists `$30 / 1M output tokens`; each image ~**1290 output tokens** (~$0.039/image). (Check your region/account for current pricing.) ([Google Developers Blog](https://developers.googleblog.com/en/introducing-gemini-2-5-flash-image/?utm_source=chatgpt.com))
    
* **Retirements:** preview image models (`gemini-2.0-flash-preview-image-generation`, `gemini-2.5-flash-image-preview`) retire **Oct 31, 2025**—use `gemini-2.5-flash-image`. ([Google Cloud](https://cloud.google.com/vertex-ai/generative-ai/docs/multimodal/image-generation?utm_source=chatgpt.com))
    
* **Watermarking:** Images include **SynthID** invisible watermark for provenance. ([Google Developers Blog](https://developers.googleblog.com/en/introducing-gemini-2-5-flash-image/?utm_source=chatgpt.com))
    

---

### 8) Vertex AI variant (if you’re on GCP)

Use the Vertex AI SDK or REST with the same model name `gemini-2.5-flash-image`; samples and quickstart in Google Cloud docs. ([Google Cloud](https://cloud.google.com/vertex-ai/generative-ai/docs/multimodal/image-generation?utm_source=chatgpt.com))

---

### 9) Common gotchas

* **No image file?** Ensure you’re reading `inlineData.data` (base64) from the first candidate and writing it as bytes. ([Google AI for Developers](https://ai.google.dev/gemini-api/docs/image-generation))
    
* **Only images back (no text):** set `responseModalities: ['Image']`. ([Google AI for Developers](https://ai.google.dev/gemini-api/docs/image-generation))
    
* **Sizes/ratios:** use `imageConfig.aspectRatio` (e.g., `"1:1"`, `"4:5"`, `"16:9"`). ([Google AI for Developers](https://ai.google.dev/gemini-api/docs/image-generation))
    

If you tell me your stack (Node, Python, or Vertex AI) and your use case (new image vs edit vs fusion), I’ll tailor a drop-in snippet for your app.