# MiniMax H3 Image to Video Audio LoRA Trainer API

> Kifundisha LoRA kinachofundisha image-to-video ya fremu ya kwanza yenye sauti kutoka kwenye klipu za video

Hufundisha LoRA kutoka kwenye zip ya klipu za video katika `training_data_url`, kwa kutumia masharti ya fremu ya kwanza ili picha tuli iweze kuhuishwa kuwa video. Seti ya data lazima iwe na video pekee. Mipangilio inajumuisha `rank` ya 8 hadi 128, `number_of_steps` hadi 15000, `number_of_frames` kutoka 22 hadi 124, `frame_rate` kutoka 8 hadi 60 na `trigger_phrase`. Hutoa uzani wa LoRA na faili la usanidi.

- Model id: `minimax/h3/i2v/trainer`
- Made by: MiniMax
- Category: Training
- Output: file
- Price: $0.01 / step (cheapest run $20.00 (20000 API credits))
- Run: `POST https://api.doitong.com/v1/run/minimax/h3/i2v/trainer`
- Quote: `POST https://api.doitong.com/v1/quote/minimax/h3/i2v/trainer`
- Docs page: https://doitong.com/sw/developers/models/minimax/h3/i2v/trainer

## Pricing

Price: **$0.01 / step**. Billed per training step (`number_of_steps`).

The full example input below costs $20.00 = 20000 API credits (2000 steps × 10 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/minimax/h3/i2v/trainer` 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 |  |  | URL ya ZIP yenye video za mafunzo katika muundo wa .mp4, .mov, .avi, au .mkv; angalau klipu 10 zinapendekezwa, na mikusanyiko mikubwa hupendelewa. Picha haziwezi kuwa nyenzo za mafunzo: seti za data za picha pekee na nyaraka zinazochanganya picha za mafunzo na video hukataliwa, ingawa baadhi ya endpoint huruhusu picha kama sidecar za conditioning. Faili za manukuu za hiari zinaweza kuambatana na klipu, huku kila faili ya maandishi ikishiriki jina la msingi la video yake. |
| `rank` |  | enum (integer) | no | `32` | `8`, `16`, `32`, `64`, `128` | Daraja la urekebishaji la LoRA, linalobadilisha matumizi makubwa ya kumbukumbu kwa uwezo mkubwa zaidi kadiri mpangilio unavyoongezeka. |
| `number_of_steps` |  | integer | no | `2000` | 1 – 15,000 | Jumla ya idadi ya hatua za mafunzo. |
| `learning_rate` |  | number | no | `0.0002` | 0.000001 – 1 | Kiwango cha kujifunza cha uboreshaji, kinachosawazisha ongezeko linalowezekana la kasi ya mafunzo dhidi ya hatari ya overfitting kinapoongezwa. |
| `number_of_frames` |  | integer | no | `73` | 22 – 124 | Idadi ya fremu kwa kila sampuli ya mafunzo; kuigawa kwa 17 lazima kuache salio la 5. Mifano ni 22, 39, 56, 73, 90, 107, na 124. |
| `frame_rate` |  | integer | no | `24` | 8 – 60 | Kasi lengwa ya fremu ya video, inayopimwa kwa fremu kwa sekunde. |
| `resolution` |  | enum (string) | no | `medium` | `low`, `medium`, `high` | Mwonekano wa mafunzo. Kuongeza mwonekano huongeza mahitaji ya kumbukumbu. |
| `aspect_ratio` |  | enum (string) | no | `16:9` | `21:9`, `16:9`, `4:3`, `1:1`, `3:4`, `9:16` | Chagua uwiano wa pande wa mafunzo kutoka seti ileile inayopatikana kupitia MiniMax H3 API. |
| `trigger_phrase` |  | string | no | `` |  | Kauli ya uanzishaji wa mtindo wa LoRA, inayowekwa mwanzoni mwa manukuu wakati wa mafunzo. |
| `first_frame_conditioning_p` |  | number | no | `0.5` | 0 – 1 | Boresha utendaji wa image-to-video kwa kuongeza mara ambazo mafunzo hutumia masharti ya fremu ya kwanza; thamani hii huweka uwezekano huo. |
| `auto_scale_input` |  | boolean | no | `false` |  | Iwapo fps lengwa na idadi ya fremu zitalinganishwa kupitia kuongeza ukubwa wa video kiotomatiki; true huwezesha marekebisho haya. |
| `split_input_into_scenes` |  | boolean | no | `true` |  | Ugawaji wa mandhari kwa video zinazozidi kizingiti cha muda, ukiwashwa wakati true. |
| `split_input_duration_threshold` |  | number | no | `30` | 1 – 60 | Kichocheo cha kugawa mandhari kinachoonyeshwa kama muda kwa sekunde: video ndefu kuliko kizingiti pekee ndizo hugawanywa. |
| `debug_dataset` |  | boolean | no | `false` |  | Hali ya ukaguzi wa uchakataji awali kwa kuangalia video, picha na manukuu kabla ya uendeshaji kamili wa mafunzo. Kuiwasha humfanya mkufunzi arudishe seti ya data ya mafunzo iliyochakatwa katika jalada linaloweza kupakuliwa kwa ukaguzi wa mikono. |
| `strict_dataset` |  | boolean | no | `false` |  | Ushughulikiaji mkali wa matatizo ya uchakataji wa awali ambayo vinginevyo yangeandikwa kwenye logi na kutatuliwa kwa kutumia fallback zilizoandikwa. Kuiwezesha hukataa manukuu yanayohitaji vidokezo tupu, keyframe za sidecar zinazokosekana, na video zenye sauti isiyosomeka badala ya kutumia kidokezo tupu, fremu ya klipu, au ukimya, mtawalia. |

## 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/minimax/h3/i2v/trainer?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/minimax/h3/i2v/trainer?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/minimax/h3/i2v/trainer", 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": "minimax/h3/i2v/trainer",
      "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": "minimax/h3/i2v/trainer",
  "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": 20000,
    "usd": "20.00",
    "charged": 20000,
    "refunded": 0
  },
  "input": {
    "training_data_url": "https://example.com/your-file.zip"
  },
  "output": {
    "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 |
|---|---|---|
| `lora_file` | object {url, content_type, file_name, file_size} | URL ya uzito wa LoRA uliofunzwa katika umbizo la .safetensors. |
| `config_file` | object {url, content_type, file_name, file_size} | Usanidi wa kuweka endpoint ya uelekezaji. |
| `debug_dataset` | object {url, content_type, file_name, file_size} \| null | Inapatikana tu kwa maombi yenye `debug_dataset` iliyowezeshwa; jalada hili linaloweza kupakuliwa huhifadhi data ya mafunzo baada ya uchakataji wa awali. |

## Related models

- [MiniMax H3 First Last Frame LoRA Trainer](https://doitong.com/developers/models/minimax/h3/flf2v/trainer.md) (`minimax/h3/flf2v/trainer`): $0.01 / step
- [MiniMax H3 Reference to Video LoRA Trainer](https://doitong.com/developers/models/minimax/h3/ref2va/trainer.md) (`minimax/h3/ref2va/trainer`): $0.015 / step
- [MiniMax H3 Text to Video LoRA Trainer](https://doitong.com/developers/models/minimax/h3/t2v/trainer.md) (`minimax/h3/t2v/trainer`): $0.005 / step
- [ERNIE-Image Trainer](https://doitong.com/developers/models/ernie-image-trainer.md) (`ernie-image-trainer`): $0.0012 / step
- [FLUX 2 \[klein\] 9b Base Trainer](https://doitong.com/developers/models/flux-2-klein-9b-base-trainer.md) (`flux-2-klein-9b-base-trainer`): $0.0043 / step
- [Flux 2 Klein 9B Base Trainer](https://doitong.com/developers/models/flux-2-klein-9b-base-trainer/edit.md) (`flux-2-klein-9b-base-trainer/edit`): $0.0139 / step
- [FLUX 2 Trainer](https://doitong.com/developers/models/flux-2-trainer.md) (`flux-2-trainer`): $0.0064 / step
- [FLUX 2 Trainer Edit](https://doitong.com/developers/models/flux-2-trainer/edit.md) (`flux-2-trainer/edit`): $0.0389 / step

## Links

- HTML page: https://doitong.com/developers/models/minimax/h3/i2v/trainer
- 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=minimax/h3/i2v/trainer
- Errors: https://doitong.com/developers/docs/errors
- Model details as JSON: https://api.doitong.com/v1/models/minimax/h3/i2v/trainer