# Wan · v2.2 5b · Text to Video · Fast Wan API

> Wan 5B texte-vidéo rapide avec sortie 480p, 580p ou 720p et interpolation facultative

Texte-vidéo utilisant la version FastVideo du modèle 5B. Il prend un `prompt` et un `negative_prompt` facultatif, avec `num_frames` de 17 à 161, `frames_per_second` de 4 à 60 et les formats 16:9, 9:16 ou 1:1. Il ajoute l’option 480p aux options 580p et 720p, ne propose pas de nombre d’étapes et prend en charge l’interpolation film ou rife.

- Model id: `wan/v2.2-5b/text-to-video/fast-wan`
- Made by: Alibaba
- Category: Text to Video
- Output: video
- Price: from $0.0125 / video (cheapest run $0.013 (13 API credits))
- Run: `POST https://api.doitong.ru/v1/run/wan/v2.2-5b/text-to-video/fast-wan`
- Quote: `POST https://api.doitong.ru/v1/quote/wan/v2.2-5b/text-to-video/fast-wan`
- Docs page: https://doitong.com/fr-CA/developers/models/wan/v2.2-5b/text-to-video/fast-wan

## Pricing

Price: **from $0.0125 / video** (the lowest tier; the quote prices your exact input). Billed once per generated video.

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

- When `resolution` = 580p: $0.0188 (18.75 API credits) / video
- When `resolution` = 720p: $0.025 (25 API credits) / video

The full example input below costs $0.025 = 25 API credits (1 video × 25 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/wan/v2.2-5b/text-to-video/fast-wan` 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 |
|---|---|---|---|---|---|---|
| `prompt` |  | string | yes |  |  | Instructions textuelles qui orientent la génération vidéo. |
| `negative_prompt` |  | string | no | `` |  | Invite négative appliquée lors de la génération d’une vidéo. |
| `num_frames` |  | integer | no | `81` | 17 – 161 | Nombre d’images pour la génération, avec une plage inclusive de 17–161. |
| `frames_per_second` |  | integer \| null | no | `24` | 4 – 60 | Cadence de la vidéo générée, acceptant des valeurs de 4 à 60; définir `adjust_fps_for_interpolation` sur false conserve cette cadence inchangée. Avec l’interpolation et `adjust_fps_for_interpolation` défini sur true (sa valeur par défaut), multipliez cette cadence par un plus le nombre d’images interpolées pour obtenir le FPS final. Par exemple, 16 FPS avec 1 image interpolée devient 32 FPS. |
| `seed` |  | integer \| null | no |  |  | Graine qui rend la génération reproductible. La définir sur None sélectionne une graine aléatoirement. |
| `resolution` |  | enum (string) | no | `720p` | `480p`, `580p`, `720p` | Résolution de sortie vidéo, soit 580p, soit 720p. |
| `aspect_ratio` |  | enum (string) | no | `16:9` | `16:9`, `9:16`, `1:1` | Rapport hauteur/largeur de la vidéo de sortie, soit 16:9, soit 9:16. |
| `enable_safety_checker` |  | boolean | no | `false` |  | Contrôle de sécurité de l’entrée avant le traitement, que seuls les comptes autorisés peuvent désactiver. Les requêtes sans autorisation sont toujours contrôlées; sinon, true active le contrôle. |
| `enable_output_safety_checker` |  | boolean | no | `false` |  | Contrôle le contrôle de sécurité de la vidéo générée; la valeur true active une vérification après la génération. |
| `enable_prompt_expansion` |  | boolean | no | `false` |  | Permet à un grand modèle de langage d'enrichir l'invite avec des détails. L'activation de cette expansion laisse le sens de l'invite inchangé. |
| `guidance_scale` |  | number | no | `3.5` | 1 – 10 | Intensité du guidage sans classifieur, qui échange une éventuelle perte de qualité contre une meilleure correspondance avec l’invite lorsque l’échelle augmente. |
| `interpolator_model` |  | enum (string) | no | `film` | `none`, `film`, `rife` | Paramètre d’interpolation d’images : choisissez None pour ignorer l’interpolation ou indiquez le modèle qui doit l’effectuer. |
| `num_interpolated_frames` |  | integer | no | `0` | 0 – 4 | Insérez 0–4 images interpolées dans chaque intervalle entre deux images générées. |
| `adjust_fps_for_interpolation` |  | boolean | no | `true` |  | Commande d’ajustement de la cadence : false conserve le FPS fourni, tandis que true le multiplie par un plus le nombre d’images interpolées. Ainsi, 16 FPS devient 32 FPS lorsqu’une image est interpolée et que l’ajustement est activé. |
| `video_quality` |  | enum (string) | no | `high` | `low`, `medium`, `high`, `maximum` | Paramètre de qualité de sortie vidéo qui échange des fichiers plus volumineux contre de meilleurs visuels à mesure que sa valeur augmente. |
| `video_write_mode` |  | enum (string) | no | `balanced` | `fast`, `balanced`, `small` | Mode d’écriture vidéo, avec balanced comme compromis entre vitesse et qualité. Choisissez small pour les fichiers les plus petits et l’écriture la plus lente; une écriture plus rapide renvoie les résultats plus tôt, mais crée des fichiers plus volumineux. |

## 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/wan/v2.2-5b/text-to-video/fast-wan?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/wan/v2.2-5b/text-to-video/fast-wan?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/wan/v2.2-5b/text-to-video/fast-wan", 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": "wan/v2.2-5b/text-to-video/fast-wan",
      "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": "wan/v2.2-5b/text-to-video/fast-wan",
  "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": 25,
    "usd": "0.025",
    "charged": 25,
    "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
    },
    "prompt": "A medium shot establishes a modern, minimalist office setting: clean lines, muted grey walls, and polished wood surfaces. The focus shifts to a close-up on a woman in sharp, navy blue business attire. Her crisp white blouse contrasts with the deep blue of her tailored suit jacket. The subtle texture of the fabric is visible—a fine weave with a slight sheen. Her expression is serious, yet engaging, as she speaks to someone unseen just beyond the frame. Close-up on her eyes, showing the intensity of her gaze and the fine lines around them that hint at experience and focus. Her lips are slightly parted, as if mid-sentence. The light catches the subtle highlights in her auburn hair, meticulously styled. Note the slight catch of light on the silver band of her watch. High resolution 4k",
    "seed": 42
  },
  "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} | Fichier vidéo produit par la génération. |
| `prompt` | string | Invite textuelle utilisée pour générer la vidéo. |
| `seed` | integer | Valeur de graine appliquée pendant la génération. |

## Related models

- [Wan 3.0 Text to Video](https://doitong.com/developers/models/alibaba/wan-3.0/text-to-video.md) (`alibaba/wan-3.0/text-to-video`): from $0.05 / second
- [FLUX 3 Max Text to Video](https://doitong.com/developers/models/blackforestlabs/flux-3-max/text-to-video.md) (`blackforestlabs/flux-3-max/text-to-video`): from $0.0425 / second of output video
- [Grok Imagine Video 1.5 Text to Video](https://doitong.com/developers/models/xai/grok-imagine-video/v1.5/text-to-video.md) (`xai/grok-imagine-video/v1.5/text-to-video`): from $0.08 / second
- [Kling 3.0 Pro Text to Video](https://doitong.com/developers/models/kling-video/v3/pro/text-to-video.md) (`kling-video/v3/pro/text-to-video`): from $0.112 / second
- [LTX 2.5 Pro Text to Video](https://doitong.com/developers/models/lightricks/ltx-2.5/text-to-video/pro.md) (`lightricks/ltx-2.5/text-to-video/pro`): from $0.12 / second
- [MiniMax H3 Text to Video](https://doitong.com/developers/models/minimax/h3/text-to-video.md) (`minimax/h3/text-to-video`): from $0.05 / second
- [Seedance 2.0 Fast Text to Video](https://doitong.com/developers/models/bytedance/seedance-2.0/fast/text-to-video.md) (`bytedance/seedance-2.0/fast/text-to-video`): from $0.113 / second
- [Seedance 2.0 Text to Video](https://doitong.com/developers/models/bytedance/seedance-2.0/text-to-video.md) (`bytedance/seedance-2.0/text-to-video`): from $0.141 / second

## Links

- HTML page: https://doitong.com/developers/models/wan/v2.2-5b/text-to-video/fast-wan
- 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=wan/v2.2-5b/text-to-video/fast-wan
- Errors: https://doitong.com/developers/docs/errors
- Model details as JSON: https://api.doitong.ru/v1/models/wan/v2.2-5b/text-to-video/fast-wan