# Luma Ray 3.2 Image to Video API

> 끝 프레임 또는 최대 64개 키프레임, 루프 및 선택적 HDR/EXR 출력을 지원하는 Ray 3.2 이미지-투-비디오

`image_url`을 첫 프레임으로 애니메이션화하고 선택적으로 `end_image_url`을 사용하거나, 대신 `keyframes`와 `keyframe_indexes` (1~64)를 사용합니다. 화면 비율은 3:4~21:9, 해상도는 540p, 720p 또는 1080p이며 `duration`은 5s 또는 10s입니다. 10s에는 키프레임이 필요합니다. `loop`, `hdr` 및 `exr_export`는 명시된 조건에서 사용할 수 있습니다. 프롬프트 제한은 6000자입니다.

- Model id: `luma/agent/ray/v3.2/image-to-video`
- Made by: Luma AI
- Category: Image to Video
- Output: video
- Price: from $0.03 / second (5 s ≈ $0.15) (cheapest run $0.15 (150 API credits))
- Run: `POST https://api.doitong.ru/v1/run/luma/agent/ray/v3.2/image-to-video`
- Quote: `POST https://api.doitong.ru/v1/quote/luma/agent/ray/v3.2/image-to-video`
- Docs page: https://doitong.com/ko/developers/models/luma/agent/ray/v3.2/image-to-video

## Pricing

Price: **from $0.03 / second (5 s ≈ $0.15)** (the lowest tier; the quote prices your exact input). Billed per second of output (`duration`, default 10).

Price rules (the first rule that matches the input wins; a parameter you leave out counts as its default):

- When `exr_export` = true and `hdr` = true and `resolution` = 1080p: $0.72 (720 API credits) / second
- When `exr_export` = true and `hdr` = true: $0.18 (180 API credits) / second
- When `hdr` = true and `resolution` = 1080p: $0.48 (480 API credits) / second
- When `hdr` = true: $0.12 (120 API credits) / second
- When `resolution` = 1080p: $0.24 (240 API credits) / second
- When `resolution` = 720p: $0.06 (60 API credits) / second

The full example input below costs $0.15 = 150 API credits (5 s × 30 API credits).

Prices are the upstream price in USD, paid from the API balance in API credits (1000 API credits = 1 USD). `POST https://api.doitong.ru/v1/quote/luma/agent/ray/v3.2/image-to-video` with the same JSON body returns the exact price for that input; the quote is exactly what a run charges. Invalid input is never charged and failed or canceled requests are refunded automatically.

## Input parameters

Send either the canonical name or the native field name (not both). Canonical names are the same across models.

| Parameter | Canonical name | Type | Required | Default | Allowed values / range | Description |
|---|---|---|---|---|---|---|
| `prompt` |  | string | yes |  | 1 – 6000 characters | 생성할 장면 또는 움직임의 텍스트 설명입니다. |
| `image_url` | `image` | string (image URL) \| null | no |  | ≥ 1 characters | image_url을 통해 제공되는 첫 프레임 이미지 URL입니다. 선택적으로 end_image_url을 함께 사용할 수 있습니다. 이 앵커 모드에서는 키프레임이 제외되므로 두 모드를 함께 사용할 수 없습니다. |
| `end_image_url` | `end_image` | string (image URL) \| null | no |  |  | image_url에서 end_image_url로 보간할 수 있게 하는 선택적 마지막 프레임 이미지 URL입니다. 키프레임을 사용하는 대신 사용할 수 있습니다. |
| `aspect_ratio` |  | enum (string) | no | `16:9` | `3:4`, `4:3`, `1:1`, `9:16`, `16:9`, `21:9` | 결과 동영상의 종횡비입니다. |
| `resolution` |  | enum (string) | no | `540p` | `540p`, `720p`, `1080p` | 출력 동영상의 해상도입니다. |
| `duration` |  | enum (string) | no | `5s` | `5s`, `10s` | 생성된 동영상의 길이입니다. 단일 image_url / end_image_url 앵커는 10s를 지원할 수 없으며, 해당 길이에는 keyframes / keyframe_indexes를 통한 여러 키프레임이 필요합니다. |
| `loop` |  | boolean | no | `false` |  | 표준 동적 범위 출력으로 제한되는 끊김 없는 루프 생성입니다. 끝 프레임 또는 키프레임을 지정하면 이 옵션을 사용할 수 없습니다. |
| `hdr` |  | boolean | no | `false` |  | MP4 출력용 HDR 인코딩입니다. HDR 액세스 권한이 있는 계정에서 720p 또는 1080p로 사용할 수 있습니다. 사용하려면 루프를 비활성화해야 합니다. |
| `exr_export` |  | boolean | no | `false` |  | MP4와 함께 내보내는 추가 EXR입니다. HDR 액세스 권한과 hdr=true가 모두 있는 경우에만 사용할 수 있습니다. |
| `keyframes` |  | array of string \| null | no |  | 1 – 64 items | 멀티 키프레임 이미지-동영상 가이드로 1–64개의 이미지 URL을 제공합니다. 위치를 지정하는 동일한 길이의 keyframe_indexes 목록도 함께 제공해야 합니다. 키프레임을 사용하면 HDR 및 10s 생성이 가능하지만 image_url, end_image_url, loop는 사용할 수 없습니다. |
| `keyframe_indexes` |  | array of integer \| null | no |  | 1 – 64 items | 키프레임과 연결된 앵커 위치입니다. 항목 [i]는 출력에서 keyframes[i]의 위치를 지정하며 두 배열의 길이는 같아야 합니다. 위치는 서로 달라야 하고 음수가 아니어야 하며, duration × 24fps의 범위는 5s에서 0–120, 10s에서 0–240입니다. |
| `enable_safety_checker` |  | boolean | no | `true` |  | 호출자에게 권한이 있으면 false로 설정해 검사를 완화할 수 있습니다. |

File parameters (`image`, `end_image`) take a public `https://` URL, a `data:` URI up to 10 MB, or the `file_url` of an upload from `POST /files`.

## Example input

Required parameters only:

```json
{
  "prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field"
}
```

A fuller example:

```json
{
  "prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field"
}
```

## Run it

Set `DOITONG_API_KEY` to a key from https://doitong.com/developers/dashboard#keys. `?wait=20` returns the finished request in the same call when it is ready within 20 seconds; otherwise poll `GET /requests/{id}` (it also accepts `?wait=`), or pass `webhook_url`.

### curl

```bash
# Run the model; wait up to 20 s for the finished result in the same call
curl -X POST "https://api.doitong.ru/v1/run/luma/agent/ray/v3.2/image-to-video?wait=20" \
  -H "Authorization: Bearer $DOITONG_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field"
  }'

# Still "queued" or "running"? Poll with the id from the response:
curl "https://api.doitong.ru/v1/requests/REQUEST_ID?wait=20" \
  -H "Authorization: Bearer $DOITONG_API_KEY"
```

### JavaScript

```javascript
const API = "https://api.doitong.ru/v1";
const headers = {
  "Authorization": "Bearer " + process.env.DOITONG_API_KEY,
  "Content-Type": "application/json",
};

// Run the model; wait up to 20 s for the finished result in the same call
let res = await fetch(API + "/run/luma/agent/ray/v3.2/image-to-video?wait=20", {
  method: "POST",
  headers,
  body: JSON.stringify({
    "prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field"
  }),
});
let request = await res.json();
if (!res.ok) throw new Error(request.error.code + ": " + request.error.message);

// Not finished yet: long-poll until it is
while (request.status === "queued" || request.status === "running") {
  res = await fetch(API + "/requests/" + request.id + "?wait=20", { headers });
  request = await res.json();
}
if (request.status !== "succeeded") throw new Error(JSON.stringify(request.error));
console.log(request.outputs.map((o) => o.url), request.cost.credits + " API credits ($" + request.cost.usd + ")");
```

### Python

```python
import os
import requests

API = "https://api.doitong.ru/v1"
headers = {"Authorization": "Bearer " + os.environ["DOITONG_API_KEY"]}

payload = {
    "prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field",
}

# Run the model; wait up to 20 s for the finished result in the same call
r = requests.post(API + "/run/luma/agent/ray/v3.2/image-to-video", params={"wait": 20}, json=payload, headers=headers)
request = r.json()
if not r.ok:
    raise RuntimeError(request["error"]["code"] + ": " + request["error"]["message"])

# Not finished yet: long-poll until it is
while request["status"] in ("queued", "running"):
    request = requests.get(API + "/requests/" + request["id"], params={"wait": 20}, headers=headers).json()
if request["status"] != "succeeded":
    raise RuntimeError(request["error"])
print([o["url"] for o in request["outputs"]], request["cost"]["credits"], "API credits", "$" + request["cost"]["usd"])
```

### MCP

The MCP server at `https://api.doitong.ru/v1/mcp` exposes the tools `search_models`, `get_model`, `quote`, `run`, `get_request`, `cancel_request`, `list_requests`, `create_upload` and `get_account`. A `run` call for this model:

```json
{
  "jsonrpc": "2.0",
  "id": 1,
  "method": "tools/call",
  "params": {
    "name": "run",
    "arguments": {
      "model_id": "luma/agent/ray/v3.2/image-to-video",
      "input": {
        "prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field"
      },
      "wait_seconds": 20
    }
  }
}
```

## Response

Every call returns a request object. `status` is one of `queued`, `running`, `succeeded`, `failed`, `canceled`. `outputs` lists the generated files with URLs on our storage (kept forever, or 7 days with `?storage=temporary`; `storage` says which); `output` is the model's own result object with the same URLs.

```json
{
  "id": "req_8k2m4q7x1z9c3v5b6n0p2r4t",
  "object": "request",
  "model": "luma/agent/ray/v3.2/image-to-video",
  "status": "succeeded",
  "created_at": "2026-10-20T12:00:00Z",
  "started_at": "2026-10-20T12:00:02Z",
  "completed_at": "2026-10-20T12:00:09Z",
  "queue_position": null,
  "cost": {
    "credits": 150,
    "usd": "0.15",
    "charged": 150,
    "refunded": 0
  },
  "input": {
    "prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field"
  },
  "output": {
    "video": {
      "url": "https://content.doitong.com/dev-api/2026/10/20/req_8k2m4q7x1z9c3v5b6n0p2r4t/0-output.mp4",
      "content_type": "video/mp4",
      "file_name": "0-output.mp4",
      "file_size": 1843200
    },
    "exr_file": {
      "url": "https://content.doitong.com/dev-api/2026/10/20/req_8k2m4q7x1z9c3v5b6n0p2r4t/0-output.mp4",
      "content_type": "video/mp4",
      "file_name": "0-output.mp4",
      "file_size": 1843200
    }
  },
  "outputs": [
    {
      "type": "video",
      "url": "https://content.doitong.com/dev-api/2026/10/20/req_8k2m4q7x1z9c3v5b6n0p2r4t/0-output.mp4",
      "content_type": "video/mp4",
      "file_size": 1843200,
      "width": 1280,
      "height": 720,
      "duration": 5,
      "stored": true
    }
  ],
  "error": null,
  "metrics": {
    "inference_seconds": 6.8
  },
  "urls": {
    "self": "https://api.doitong.ru/v1/requests/req_8k2m4q7x1z9c3v5b6n0p2r4t",
    "cancel": "https://api.doitong.ru/v1/requests/req_8k2m4q7x1z9c3v5b6n0p2r4t/cancel"
  }
}
```

### Output fields (`output`)

| Field | Type | Description |
|---|---|---|
| `video` | object {url, content_type, file_name, file_size} | 모델이 생성한 동영상입니다. |
| `exr_file` | object {url, content_type, file_name, file_size} \| null | Luma가 내보내는 형식의 EXR 사이드카입니다. 하나의 EXR 파일 또는 ZIP 아카이브일 수 있으며 exr_export가 true일 때 생성됩니다. |

## Related models

- [Luma Ray 3.2 Text to Video](https://doitong.com/developers/models/luma/agent/ray/v3.2/text-to-video.md) (`luma/agent/ray/v3.2/text-to-video`): from $0.10 / second
- [Luma Ray 3.2 Reframe](https://doitong.com/developers/models/luma/agent/ray/v3.2/reframe.md) (`luma/agent/ray/v3.2/reframe`): from $0.06 / second of input video
- [Luma Ray 3.2 Video to Video](https://doitong.com/developers/models/luma/agent/ray/v3.2/video-to-video.md) (`luma/agent/ray/v3.2/video-to-video`): from $0.144 / second
- [FLUX 3 Max Image to Video](https://doitong.com/developers/models/blackforestlabs/flux-3-max/image-to-video.md) (`blackforestlabs/flux-3-max/image-to-video`): from $0.0425 / second of output video
- [Grok Imagine Video 1.5 Image to Video](https://doitong.com/developers/models/xai/grok-imagine-video/v1.5/image-to-video.md) (`xai/grok-imagine-video/v1.5/image-to-video`): from $0.082 / second
- [Kling 3.0 Pro Image to Video](https://doitong.com/developers/models/kling-video/v3/pro/image-to-video.md) (`kling-video/v3/pro/image-to-video`): from $0.112 / second
- [LTX 2.5 Pro Image to Video](https://doitong.com/developers/models/lightricks/ltx-2.5/image-to-video/pro.md) (`lightricks/ltx-2.5/image-to-video/pro`): from $0.12 / second
- [MiniMax H3 Image to Video](https://doitong.com/developers/models/minimax/h3/image-to-video.md) (`minimax/h3/image-to-video`): from $0.05 / second

## Links

- HTML page: https://doitong.com/developers/models/luma/agent/ray/v3.2/image-to-video
- All models and guides for AI agents: https://doitong.com/developers/llms.txt
- OpenAPI 3.1 with this model's typed request body: https://doitong.com/developers/openapi.json?model=luma/agent/ray/v3.2/image-to-video
- Errors: https://doitong.com/developers/docs/errors
- Model details as JSON: https://api.doitong.ru/v1/models/luma/agent/ray/v3.2/image-to-video