# Google Veo 3 Fast — Reference To Video

> Access Veo 3 Fast video capabilities for rapid, cinematic production. Generate text-to-video with native audio and high temporal consistency at GPTProto.com.

## Overview

- **Endpoint**: `POST https://gptproto.com/api/v3/google/veo3-fast/reference-to-video`
- **Query endpoint**: `POST https://gptproto.com/api/v3/predictions/{{id}}/result`
- **Model ID**: `veo3-fast`
- **Vendor**: Google
- **Scene**: `reference-to-video`
- **Category**: image-to-video
- **Modalities**: input image → output video
- **Model page**: https://gptproto.com/model/google/veo3-fast/reference-to-video
- **API documentation**: https://docs.gptproto.com/docs/allapi/Google/veo3-fast/gptproto-format/reference-to-video
- **Other scenes of this model**: `text-to-video`, `image-to-video` — same auth, different endpoint path and input schema

## Authentication

Every request needs a GPTProto API key. Create one at https://gptproto.com/dashboard/api-key, then export it:

```bash
export GPTPROTO_API_KEY="your-api-key"
```

Header: `Authorization: Bearer $GPTPROTO_API_KEY`.

## Pricing

Platform price by tier (USD, already includes the GPTProto discount):

- **Per run** — $0.48 per run

Price range: $0.48 – $0.48 per generation.

Prices may change. The model page always shows the live price: https://gptproto.com/model/google/veo3-fast/reference-to-video

## API Information

The examples below use this model's official request format. Submit the first request, then poll the query endpoint until the vendor operation finishes.

### Input Schema

The accepted JSON body is the official request shape below:

**Full Example**:

```json
{
  "prompt": "A young woman walks alone under a transparent umbrella in a quiet alley during light rain, soft city lights reflecting on the wet pavement. Her pace is calm and thoughtful. The camera follows slowly behind her, occasional droplets hitting the lens. Subtle piano music plays, evoking a melancholic but peaceful mood. Dreamy, cinematic, slightly slow motion.",
  "images": [
    "https://oss.gptproto.com/2025/11/12/d5c2f08479b9452aacbcf9963631ce21.jpeg"
  ],
  "aspect_ratio": "16:9",
  "enhance_prompt": true
}
```

## Usage Examples

### 1. Submit a request

```bash
curl --request POST "https://gptproto.com/api/v3/google/veo3-fast/reference-to-video" \
    --header "Authorization: Bearer $GPTPROTO_API_KEY" \
    --header "Content-Type: application/json" \
    --data '{
        "prompt": "A young woman walks alone under a transparent umbrella in a quiet alley during light rain, soft city lights reflecting on the wet pavement. Her pace is calm and thoughtful. The camera follows slowly behind her, occasional droplets hitting the lens. Subtle piano music plays, evoking a melancholic but peaceful mood. Dreamy, cinematic, slightly slow motion.",
        "images": [
            "https://oss.gptproto.com/2025/11/12/d5c2f08479b9452aacbcf9963631ce21.jpeg"
        ],
        "aspect_ratio": "16:9",
        "enhance_prompt": true
    }'
```

```python
import os
import requests

url = "https://gptproto.com/api/v3/google/veo3-fast/reference-to-video"
headers = {
    "Authorization": f"Bearer {os.environ['GPTPROTO_API_KEY']}",
    "Content-Type": "application/json"
}
payload = {
    "prompt": "A young woman walks alone under a transparent umbrella in a quiet alley during light rain, soft city lights reflecting on the wet pavement. Her pace is calm and thoughtful. The camera follows slowly behind her, occasional droplets hitting the lens. Subtle piano music plays, evoking a melancholic but peaceful mood. Dreamy, cinematic, slightly slow motion.",
    "images": [
        "https://oss.gptproto.com/2025/11/12/d5c2f08479b9452aacbcf9963631ce21.jpeg"
    ],
    "aspect_ratio": "16:9",
    "enhance_prompt": True
}

response = requests.request("POST", url, headers=headers, json=payload)
print(response.json())
```

```typescript
const response = await fetch("https://gptproto.com/api/v3/google/veo3-fast/reference-to-video", {
    method: "POST",
    headers: {
        "Authorization": `Bearer ${process.env.GPTPROTO_API_KEY}`,
        "Content-Type": "application/json",
    },
    body: JSON.stringify({
        prompt: "A young woman walks alone under a transparent umbrella in a quiet alley during light rain, soft city lights reflecting on the wet pavement. Her pace is calm and thoughtful. The camera follows slowly behind her, occasional droplets hitting the lens. Subtle piano music plays, evoking a melancholic but peaceful mood. Dreamy, cinematic, slightly slow motion.",
        images: [
            "https://oss.gptproto.com/2025/11/12/d5c2f08479b9452aacbcf9963631ce21.jpeg",
        ],
        aspect_ratio: "16:9",
        enhance_prompt: true,
    }),
});

const data = await response.json();
console.log(data);
```

### 2. Check status

Replace `{{operation_id}}` (or the operation name in the URL) with the value returned by the submit request, and keep polling until the operation completes.

```bash
curl --request POST "https://gptproto.com/api/v3/predictions/{{id}}/result" \
    --header "Authorization: Bearer $GPTPROTO_API_KEY" \
    --header "Content-Type: application/json"
```

```python
import os
import requests

url = "https://gptproto.com/api/v3/predictions/{{id}}/result"
headers = {
    "Authorization": f"Bearer {os.environ['GPTPROTO_API_KEY']}",
    "Content-Type": "application/json"
}

response = requests.request("POST", url, headers=headers)
print(response.json())
```

```typescript
const response = await fetch("https://gptproto.com/api/v3/predictions/{{id}}/result", {
    method: "POST",
    headers: {
        "Authorization": `Bearer ${process.env.GPTPROTO_API_KEY}`,
        "Content-Type": "application/json",
    },
});

const data = await response.json();
console.log(data);
```

## Example Prompts

- Make the dog run further.
- /
- After cracks appear on the rabbit mask, new vines grow from its eye sockets.

## HTTP Status Codes

- `400` — malformed body, a parameter or value this model does not accept, or input blocked by the provider's content moderation
- `401` — missing or invalid API key
- `403` — insufficient credits
- `413` — request body too large
- `429` — rate limited; retry with backoff
- `500` — An internal server error occurred
- `502` — An internal server error occurred
- `504` — Gateway timeout — upstream service did not respond in time; retry later

## Additional Resources

- [Model page](https://gptproto.com/model/google/veo3-fast/reference-to-video)
- [API documentation](https://docs.gptproto.com/docs/allapi/Google/veo3-fast/gptproto-format/reference-to-video)
- [All models](https://gptproto.com/model)
- [API keys](https://gptproto.com/dashboard/api-key)
- [Platform overview for LLMs](https://gptproto.com/llms-full.txt)
- Any other model: `https://gptproto.com/model/{vendor}/{model}/{scene}/llms.txt`