# LTX 2.3 Trainer (V2) - Keyframe Interpolation API

> ᠵᠠᠯᠠᠨᡳ ᠵᠠᠯᠠᠨ ᠵᡳᠯᡤᠠᠨᡳ ᠵᠠᠪᡩᡠ ᠪᡝ ᠪᠠᠶᠠᠨ ᠪᡠᠮᡝ ᠵᠠᠯᠠᠨᡳ ᠵᠠᠩ ᠪᡝ ᠪᠠᠶᠠᠨ ᠪᡠᠮᡝ ᠪᠠᠶᠠᠯᠠᠮᠪᡳ᠂ ᠵᡠᠸᡝᠴᡳ ᠵᡠᠸᡝ ᠪᡝ ᠵᠠᠯᠠᠨ ᠵᠠᠪᡩᡠ ᠪᡝ ᠪᠠᠶᠠᠨ ᠪᡠᠮᡝ

ᠵᠠᠯᠠᠨ ᠵᠠᠩᡳ ᠵᠠᠪᡩᡠ ᠵᠠᠯᠠᠨ ᠵᠠᠪᡩᡠ ᠪᡝ ᠵᠠᠯᠠᠨ ᠪᡝ ᠪᠠᠶᠠᠨ ᠪᡠᠮᡝ ᠪᠠᠶᠠᠯᠠᠮᠪᡳ: ᠵᠠᠯᠠᠨ ᡳ ᠪᡠᠶᡝᠨ ᡩᡝ ᠵᠠᠯᠠᠨᡳ ᠵᠠᠪᡩᡠ ᠪᠠ ᡝᠯᡝᠨᡳ ᠵᠠᠪᡩᡠ ᠪᡝ ᠪᡠᠮᡝ ᠵᠠᠯᠠᠨ ᠪᡝ ᠪᠠᠶᠠᠨ ᠪᡠᠮᡝ ᠪᠠᠶᠠᠯᠠᠮᠪᡳ᠃ `include_middle_keyframe` ᡝᠯᡝ ᠵᠠᠪᡩᡠ ᠪᡝ ᠵᠠᠩ ᡩᡝ ᠠᠪᡠᠮᠪᡳ; ᠪᠠᠶᠠᠯᠠᠨᡳ ᠵᠠᠩ ᡝᠮᡠ ᡳᠨᡠ `middle_image_url` ᠪᡝ ᠠᠪᡠᠮᠪᡳ᠃ ᠵᠠᠩ ᠪᡝ `training_data_url` ᡳ ᠵᡠᠪᡝᠨ ᡩᡝ ᠠᠪᡠᠮᠪᡳ᠂ ᠪᠠᠶᠠᠯᠠᠨ ᡩᡝ 2 ᠵᠠᠩ ᡩᡝ ᠣᠯᡥᠣᠪᡠᠮᠪᡳ᠃

- Model id: `ltx23-trainer-v2/interpolate`
- Made by: Lightricks
- Category: Training
- Output: file
- Price: $0.0024 / step (cheapest run $4.80 (4800 API credits))
- Run: `POST https://api.doitong.com/v1/run/ltx23-trainer-v2/interpolate`
- Quote: `POST https://api.doitong.com/v1/quote/ltx23-trainer-v2/interpolate`
- Docs page: https://doitong.com/mnc/developers/models/ltx23-trainer-v2/interpolate

## Pricing

Price: **$0.0024 / step**. Billed per training step (`number_of_steps`).

The full example input below costs $4.80 = 4800 API credits (2000 steps × 2.4 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.com/v1/quote/ltx23-trainer-v2/interpolate` 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

| Parameter | Canonical name | Type | Required | Default | Allowed values / range | Description |
|---|---|---|---|---|---|---|
| `training_data_url` |  | string | yes |  |  | ᡝᡵᡝᠮᡝ ᠪᡠᠮᡝ ᡳ ᠵᡠᠯᡤᠠᠨ `.zip`, ᡳ ᡩᠠᠯᡳᠮᡝ ᡳ ᡩᠠᠯᡳᠮᡝ ᡩᠠᠯᡳᠮᡝ. ᡶᡳᠯᡝ ᡳ ᠵᡠᠯᡤᠠᠨ `.txt` ᡳ ᠮᠠᠩᡤᠠ. |
| `rank` |  | enum (integer) | no | `32` | `8`, `16`, `32`, `64`, `128` | LoRA ᡳ ᡝᡵᡝᠮᡝ ᡳ ᡩᠠᠯᡳᠮᡝ ᡩᠠᠯᡳᠮᡝ ᡳ ᠵᡠᠯᡤᠠᠨ. |
| `number_of_steps` |  | integer | no | `2000` | 100 – 10,000 | ᡩᠠᠯᡳᠮᡝ ᡳ ᡩᠠᠯᡵᡝ ᡳ ᡩᡠᠮᡝ. |
| `learning_rate` |  | number | no | `0.0002` | 0.000001 – 1 | ᡩᠠᠯᡳᠮᡝ ᡳ ᠰᡠᠯᡤᠠᠨ ᡳ ᡵᠠᠰᡠ. |
| `number_of_frames` |  | integer | no | `89` | 9 – 121 | ᡩᠠᠯᡳᠮᡝ ᡳ ᡳᠯᡝᠨ ᡳ ᡶᡳᠯᡝᠮᡝ ᡳ ᡩᡠᠮᡝ. 8 ᡩᡝ ᡩᠠᠯᡳᠮᡝ ᡳ ᡶᡠᠯᡤᠠᠨ 1 ᠣᠮᡝ; 1, 9, 17, 25, 33, 41, 49, 57, 65, 73, 81, 89, 97. |
| `frame_rate` |  | integer | no | `24` | 8 – 60 | ᡩᠠᠯᡳᠮᡝ ᡳ ᠰᡠᠨᡤᠠ ᡳ ᡶᡳᠯᡝᠮᡝ ᡳ ᠰᡝᠮᡝᠨ. LTX-2.3 ᡳ ᡝᠯᡝᠮᡝ 24. |
| `resolution` |  | enum (string) | no | `medium` | `low`, `medium`, `high` | ᡩᠠᠯᡳᠮᡝ ᡳ ᠵᠠᠯᠠᠨ. ᠵᠠᠯᠠᠨ ᡳ ᠠᠯᡳᠮᡝ ᡳ ᠮᡝᠮᡝᠨᡳ ᡩᠠᠯᡳᠮᡝ. |
| `aspect_ratio` |  | enum (string) | no | `1:1` | `16:9`, `1:1`, `9:16` | ᡩᠠᠯᡳᠮᡝ ᡳ ᡳᠯᡤᠠᠨ ᡳ ᡵᠠᠰᡠ. |
| `trigger_phrase` |  | string | no | `` |  | LoRA ᡳ ᡥᡡᠯᠠᠨ ᡳ ᠮᠠᠩᡤᠠ ᠵᡠᠰᡝᠨ. |
| `auto_scale_input` |  | boolean | no | `false` |  | ᠰᡠᠨᡤᠠ ᡳ FPS ᠠᠮᠠ ᡶᡳᠯᡝᠮᡝ ᡳ ᡩᡠᠮᡝ ᡩᡝ ᡝᡵᡝᠮᡝ ᠠᠯᡳᠮᡝ; ᡤᠠᠳᠠᠨ ᡳ ᡩᠠᠯᡳᠮᡝ ᠠᡴᡡ. |
| `split_input_into_scenes` |  | boolean | no | `true` |  | ᠵᠠᠯᠠᠨ ᠵᡠᠯᡝᠨᡳ ᠠᠴᠠᠨ ᠠᠮᠪᠠ ᠰᡠᠨᡤᠠ ᠵᠠᠯᠠᠨ ᠪᡝ ᠵᠠᠯᠠᠨ ᠮᡝᡳᠯᡝᠮᠪᡳ᠉ true ᠪᡝ ᠵᠠᠯᠠᠨ ᠮᡠᠶᠠᡥᠠᠨ ᠪᡝ ᠠᠯᡤᠠᠮᠪᡳ᠉ |
| `split_input_duration_threshold` |  | number | no | `30` | 1 – 60 | ᠵᡠᠯᡤᠠᠨ ᡳ ᡶᡠᠯᡤᠠᠨ ᡳ ᠵᡠᠸᠠᠨ, ᠰᡝᡴᡠᠨᡩ ᡳ ᠰᡝᠮᡝᠨ: ᡝᠯᡝᠮᡝ ᡳ ᠵᡠᠯᡤᠠᠨ ᡩᡝ ᡶᡠᠯᡤᠠᠨ. |
| `debug_dataset` |  | boolean | no | `false` |  | ᡩᠠᠯᡳᠮᡝ ᡳ ᡩᠠᠯᡳᠮᡝ ᡳ ᡤᠠᠳᠠᠨ, ᠰᡠᠨᡤᠠ, ᡥᡡᠯᠠᠨ ᡳ ᡳᠯᡝᠮᡝ ᡩᡝ ᠰᠠᠨᠠ. ᠵᡠᠰᡳᠯᡝᠮᡝ ᡳ ᡶᡳᠯᡝ ᡳ ᡩᠠᠯᡳᠮᡝ ᠵᡠᠯᡤᠠᠨ ᡳ ᡩᠠᠯᡳᠮᡝ ᡩᡝ ᡩᠠᠯᡳᠮᡝ ᠪᡠᠶᡝᠮᡝ. |
| `validation` |  | array of object {prompt, start_image_url, end_image_url, middle_image_url} | no | `[]` | ≤ 2 items | ᠵᡠᠯᡝᠨ ᠪᠠᡳᠮᠪᡳ; ᠵᡠᠯᡝᠨ ᡥᡡᠯᠠᠨ ᠪᡝ ᠵᡠᠯᡝᠨᡳ ᡤᠠᠳᠠᠨ ᠪᠠᡳᠮᠪᡳ᠉ |
| `validation[].prompt` |  | string | yes |  |  | ᡩᠠᠯᡳᠮᡝ ᡩᡝ ᠣᠮᡝ ᡥᡡᠯᠠᠨ. |
| `validation[].start_image_url` |  | string (image URL) | yes |  | ≥ 1 characters | ᠵᡠᠯᡝᠨᡳ ᡶᡳᠯᡝᠮᡝᡳ ᡤᠠᠳᠠᠨ URL. |
| `validation[].end_image_url` |  | string (image URL) | yes |  | ≥ 1 characters | ᠪᡠᡵᡳᠨᡳ ᡶᡳᠯᡝᠮᡝᡳ ᡤᠠᠳᠠᠨ URL. |
| `validation[].middle_image_url` |  | string (image URL) \| null | no |  |  | first+middle+last ᠵᡝᡵᡤᡳ ᠵᠠᠯᠠᠨᡳ ᠮᡝᡳᠯᡝᠮᡝᡳ ᠮᡳᡩᡝᠯᡝ ᡶᡳᠯᡝᠮᡝᡳ ᡤᠠᠳᠠᠨ URL. `include_middle_keyframe=true` ᠪᡝ ᠪᠠᡳᠮᠪᡳ; ᠠᡴᡡ ᠪᡝ ᠵᡠᠯᡝ ᠪᡠᠮᡝᠮᠪᡳ᠉ |
| `validation_negative_prompt` |  | string | no | `blurry, out of focus, overexposed, underexposed, low contrast, washed out colors, excessive noise, grainy texture, poor lighting, flickering, motion blur, distorted proportions, unnatural skin tones, deformed facial features, asymmetrical face, missing facial features, extra limbs, disfigured hands, wrong hand count, artifacts around text, inconsistent perspective, camera shake, incorrect depth of field, background too sharp, background clutter, distracting reflections, harsh shadows, inconsistent lighting direction, color banding, cartoonish rendering, 3D CGI look, unrealistic materials, uncanny valley effect, incorrect ethnicity, wrong gender, exaggerated expressions, wrong gaze direction, mismatched lip sync, silent or muted audio, distorted voice, robotic voice, echo, background noise, off-sync audio, incorrect dialogue, added dialogue, repetitive speech, jittery movement, awkward pauses, incorrect timing, unnatural transitions, inconsistent framing, tilted camera, flat lighting, inconsistent tone, cinematic oversaturation, stylized filters, or AI artifacts.` |  | ᡩᠠᠯᡳᠮᡝ ᡩᡝ ᠠᠯᡳᠮᡝ ᡳ ᠨᠠᡩᠠᠨ ᡥᡡᠯᠠᠨ. ᡝᠮᡠ ᡩᠠᠯᡳᠮᡝ ᡳ ᠵᡠᠯᡤᠠᠨ ᡳ ᠪᡠᠶᡝᠮᡝ ᡩ᠝ ᡩᠠᠯᡳᠮᡝ, ᡳᠨᡠ ᡵᠠᠰᡠ ᠠᠮᠠ ᡶᡠᠯᡤᠠᠨ ᡳ ᠠᠯᡳᠨ. |
| `validation_number_of_frames` |  | integer | no | `89` | 9 – 121 | ᡩᠠᠯᡳᠮᡝ ᡳ ᡶᡳᠯᡝᠮᡝ ᡳ ᡩᡠᠮᡝ. |
| `validation_frame_rate` |  | integer | no | `24` | 8 – 60 | ᡩᠠᠯᡳᠮᡝ ᡳ ᠰᡠᠨᡤᠠ ᡳ ᠰᡝᠮᡝᠨ; LTX-2.3 ᡳ ᡝᠯᡝᠮᡝ 24. |
| `validation_resolution` |  | enum (string) | no | `high` | `low`, `medium`, `high` | ᡩᠠᠯᡳᠮᡝ ᡩᡝ ᠣᠮᡝ ᡳ ᠵᠠᠯᠠᠨ. |
| `validation_aspect_ratio` |  | enum (string) | no | `1:1` | `16:9`, `1:1`, `9:16` | ᡩᠠᠯᡳᠮᡝ ᡩᡝ ᠣᠮᡝ ᡳ ᡳᠯᡤᠠᠨ ᡳ ᡵᠠᠰᡠ. |
| `stg_scale` |  | number | no | `1` | 0 – 3 | Spatio-Temporal Guidance (STG) ᡳ ᠵᠠᠯᠠᠨ, 1.0 ᡳ ᡩᠠᠯᡳᠮᡝ, 0.0 ᡳ STG ᡳ ᠠᡴᡡ. |
| `include_middle_keyframe` |  | boolean | no | `false` |  | ᠰᡠᠨᡤᠠ ᠪᡠᠶᡝᠮᡝᡳ ᡩᡠᠮᡝ ᡶᡳᠯᡝᠮᡝ ᡳᠯᡳᠮᠪᡠᡵᡝᠩᡤᡝ: true ᠣᠮᠪᡳ᠉ ᠵᠠᠯᠠᠨᠠᠮᠪᡠᡵᡝ ᡶᡳᠯᡝᠮᡝ ᠪᡝᡳ `middle_image_url` ᡳ ᡳᠯᡳᠮᠪᡠᠮᠪᡳ᠉ ᡝᠮᡠᠪᡝ ᠵᠠᡴᠠᠨ ᡶᡳᠯᡝᠮᡝ ᠵᡠᠯᡝ ᠸᠠᡴᠠ ᠵᡠᠯᡝ ᡥᡡᠯᠠᠨ ᠪᡝ ᠠᠯᡥᠠᠨ ᡴᡝᠮᡠᠨᡳ ᠠᡩᠠᠯᡳ ᠪᡠᠶᡝᠮᡝᠮᠪᡳ᠉ |

## Example input

Required parameters only:

```json
{
  "training_data_url": "https://example.com/your-file.zip"
}
```

A fuller example:

```json
{
  "training_data_url": "https://example.com/your-file.zip"
}
```

## 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.com/v1/run/ltx23-trainer-v2/interpolate?wait=20" \
  -H "Authorization: Bearer $DOITONG_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "training_data_url": "https://example.com/your-file.zip"
  }'

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

### JavaScript

```javascript
const API = "https://api.doitong.com/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/ltx23-trainer-v2/interpolate?wait=20", {
  method: "POST",
  headers,
  body: JSON.stringify({
    "training_data_url": "https://example.com/your-file.zip"
  }),
});
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.com/v1"
headers = {"Authorization": "Bearer " + os.environ["DOITONG_API_KEY"]}

payload = {
    "training_data_url": "https://example.com/your-file.zip",
}

# Run the model; wait up to 20 s for the finished result in the same call
r = requests.post(API + "/run/ltx23-trainer-v2/interpolate", 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.com/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": "ltx23-trainer-v2/interpolate",
      "input": {
        "training_data_url": "https://example.com/your-file.zip"
      },
      "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": "ltx23-trainer-v2/interpolate",
  "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": 4800,
    "usd": "4.80",
    "charged": 4800,
    "refunded": 0
  },
  "input": {
    "training_data_url": "https://example.com/your-file.zip"
  },
  "output": {
    "video": {
      "url": "https://content.doitong.com/dev-api/2026/10/20/req_8k2m4q7x1z9c3v5b6n0p2r4t/0-output.jpeg",
      "content_type": "image/jpeg",
      "file_name": "0-output.jpeg",
      "file_size": 1843200
    },
    "audio": {
      "url": "https://content.doitong.com/dev-api/2026/10/20/req_8k2m4q7x1z9c3v5b6n0p2r4t/0-output.jpeg",
      "content_type": "image/jpeg",
      "file_name": "0-output.jpeg",
      "file_size": 1843200
    },
    "lora_file": {
      "url": "https://content.doitong.com/dev-api/2026/10/20/req_8k2m4q7x1z9c3v5b6n0p2r4t/0-output.jpeg",
      "content_type": "image/jpeg",
      "file_name": "0-output.jpeg",
      "file_size": 1843200
    },
    "config_file": {
      "url": "https://content.doitong.com/dev-api/2026/10/20/req_8k2m4q7x1z9c3v5b6n0p2r4t/0-output.jpeg",
      "content_type": "image/jpeg",
      "file_name": "0-output.jpeg",
      "file_size": 1843200
    },
    "debug_dataset": {
      "url": "https://content.doitong.com/dev-api/2026/10/20/req_8k2m4q7x1z9c3v5b6n0p2r4t/0-output.jpeg",
      "content_type": "image/jpeg",
      "file_name": "0-output.jpeg",
      "file_size": 1843200
    }
  },
  "outputs": [
    {
      "type": "file",
      "url": "https://content.doitong.com/dev-api/2026/10/20/req_8k2m4q7x1z9c3v5b6n0p2r4t/0-output.jpeg",
      "content_type": "image/jpeg",
      "file_size": 1843200,
      "stored": true
    }
  ],
  "error": null,
  "metrics": {
    "inference_seconds": 6.8
  },
  "urls": {
    "self": "https://api.doitong.com/v1/requests/req_8k2m4q7x1z9c3v5b6n0p2r4t",
    "cancel": "https://api.doitong.com/v1/requests/req_8k2m4q7x1z9c3v5b6n0p2r4t/cancel"
  }
}
```

### Output fields (`output`)

| Field | Type | Description |
|---|---|---|
| `video` | object {url, content_type, file_name, file_size} \| null | ᡩᠠᠯᡳᠮᡝ ᡳ ᠵᠠᠯᠠᠨ ᡳ ᠰᡠᠨᡤᠠ ᡳ ᡩᠠᠯᡳᠮᡝ ᡳ ᠠᠯᡳᠨ ᡩᡝ ᡩᠠᠯᡳᠮᡝ ᠪᡠᠶᡝᠮᡝ. |
| `audio` | object {url, content_type, file_name, file_size} \| null | ᡩᠠᠯᡳᠮᡝ ᡳ ᡤᡳᠰᡠᠨ ᡳ ᠪᡠᠶᡝᠮᡝ, ᡝᡵᡝᠮᡝ ᡳ ᡩᠠᠯᡳᠮᡝ: /audio-inpaint, /audio-extend-suffix, /audio-extend-prefix, /t2a, /a2a, /v2a. |
| `lora_file` | object {url, content_type, file_name, file_size} | ᡩᠠᠯᡳᠮᡝ LoRA ᡳ ᡵᠠᠰᡠ URL, .safetensors ᡶᡳᠯᡝ. |
| `config_file` | object {url, content_type, file_name, file_size} | ᡩᠠᠯᡳᠮᡝ ᡳ ᠵᠠᠯᡳᠨ ᡳ ᠪᠠᡳᡵᡝᠨ ᡳ ᡶᡠᠯᡤᠠᠨ. |
| `debug_dataset` | object {url, content_type, file_name, file_size} \| null | `debug_dataset` ᡳ ᡩᠠᠯᡳᠮᡝ ᡩᡝ ᠣᠮᡝ ᡳ ᡶᡳᠯᡝ ᡳ ᡩᠠᠯᡳᠮᡝ ᡳ ᠪᡠᠶᡝᠮᡝ ᡩ᠝ ᡩᠠᠯᡳᠮᡝ ᡳ ᠮᠠᠩᡤᠠ. |

## Related models

- [LTX 2.3 Trainer (V2) - Audio Inpainting](https://doitong.com/developers/models/ltx23-trainer-v2/audio-inpaint.md) (`ltx23-trainer-v2/audio-inpaint`): $0.0023 / step
- [LTX 2.3 Trainer (V2) - Audio+Video Reference IC-LoRA](https://doitong.com/developers/models/ltx23-trainer-v2/ic-lora/av2av.md) (`ltx23-trainer-v2/ic-lora/av2av`): $0.0068 / step
- [LTX 2.3 Trainer (V2) - Audio+Video Reference Transformation](https://doitong.com/developers/models/ltx23-trainer-v2/av2av.md) (`ltx23-trainer-v2/av2av`): $0.0068 / step
- [LTX 2.3 Trainer (V2) - Audio-to-Audio](https://doitong.com/developers/models/ltx23-trainer-v2/a2a.md) (`ltx23-trainer-v2/a2a`): $0.0023 / step
- [LTX 2.3 Trainer (V2) - Audio-to-Audio IC-LoRA](https://doitong.com/developers/models/ltx23-trainer-v2/ic-lora/a2a.md) (`ltx23-trainer-v2/ic-lora/a2a`): $0.0023 / step
- [LTX 2.3 Trainer (V2) - Audio-to-Video](https://doitong.com/developers/models/ltx23-trainer-v2/a2v.md) (`ltx23-trainer-v2/a2v`): $0.006 / step
- [LTX 2.3 Trainer (V2) - Backward Audio Extension](https://doitong.com/developers/models/ltx23-trainer-v2/audio-extend-suffix.md) (`ltx23-trainer-v2/audio-extend-suffix`): $0.0023 / step
- [LTX 2.3 Trainer (V2) - Backward Video Extension](https://doitong.com/developers/models/ltx23-trainer-v2/extend-suffix.md) (`ltx23-trainer-v2/extend-suffix`): $0.0061 / step

## Links

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- Model details as JSON: https://api.doitong.com/v1/models/ltx23-trainer-v2/interpolate