# FLUX.1 [dev] with Controlnets and Loras · Differential Diffusion API

> FLUX.1 [dev] whakatika atahanga mā tētahi mahere panoni e tautuhi ana i te kaha whakarerekē o ia rohe

Ka panoni i ngā rohe o tētahi atahanga takenga, mā te whakamahi i tētahi atahanga mahere panoni hei whakahaere i te nui o te whakarerekētanga o ia wāhi. Me whai `prompt`, `image_url` me `change_map_image_url`. Ka menerima hoki i ngā LoRA, ControlNet, IP-Adapter me tētahi atahanga tohutoro. Ka haere `num_inference_steps` mai i te 1 ki te 50, ā, tae atu `num_images` ki te 10, me te putanga png, jpeg rānei.

- Model id: `flux-general/differential-diffusion`
- Made by: Black Forest Labs
- Category: Image Editing
- Output: image
- Estimated price per run: $0.138 / image (cheapest run $0.138 (138 API credits))
- Run: `POST https://api.doitong.com/v1/run/flux-general/differential-diffusion`
- Quote: `POST https://api.doitong.com/v1/quote/flux-general/differential-diffusion`
- Docs page: https://doitong.com/mi/developers/models/flux-general/differential-diffusion

## Pricing

Price: **$0.138 / image**. Estimated from the typical cost of one run, per output (`num_images`). The quote is exactly what the run charges.

The full example input below costs $0.138 = 138 API credits (1 image × 138 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/flux-general/differential-diffusion` 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 |  |  | Te tohutohu e ārahi ana i te whakaputanga atahanga. |
| `image_size` |  | object {width, height} \| enum (string) | no |  | `square_hd`, `square`, `portrait_4_3`, `portrait_16_9`, `landscape_4_3`, `landscape_16_9` | Ngā inenga o te atahanga kua whakaputaina. |
| `num_inference_steps` |  | integer | no | `28` | 1 – 50 | Tau o ngā hipanga whakatauira hei whakahaere. |
| `seed` |  | integer \| null | no |  |  | Kākano mō ngā atahanga ka taea te whakahoki anō: mā te tohutohu me te kākano ōrite ka puta he atahanga ōrite ina kāore te putanga tauira i whakarerekēhia. |
| `loras` |  | array of object {path, scale} | no | `[]` |  | Ngā LoRA ka whakakotahi te pānga hei whakaputa i te atahanga, kāore he here ki te maha ka tukuna. |
| `loras[].path` |  | string | yes |  |  | Wāhi o ngā taumaha LoRA, ka tauwhāitihia hei URL, hei ara rānei. |
| `loras[].scale` |  | object \| number | no | `1` |  | Te tauine mō ngā taumaha LoRA i mua i te hanumi ki te tauira pūtake. Tukuna he papakupu o te momo {"layer_name":layer_scale} hei tautuhi i ngā tauine paparanga takitahi; ka whakamahi ngā paparanga kāore i tautuhia i te 1.0. |
| `control_loras` |  | array of object {path, scale, control_image_url, preprocess} | no | `[]` |  | Ngā LoRA atahanga whakahaere kua hanumia ki tētahi whirihoranga kotahi mō te whakaputa i te atahanga whakamutunga; kāore he here ki te maha. |
| `control_loras[].path` |  | string | yes |  |  | Wāhi o ngā taumaha LoRA, ka tauwhāitihia hei URL, hei ara rānei. |
| `control_loras[].scale` |  | object \| number | no | `1` |  | Te tauine mō ngā taumaha LoRA i mua i te hanumi ki te tauira pūtake. Tukuna he papakupu o te momo {"layer_name":layer_scale} hei tautuhi i ngā tauine paparanga takitahi; ka whakamahi ngā paparanga kāore i tautuhia i te 1.0. |
| `control_loras[].control_image_url` |  | string (image URL) | yes |  |  | URL atahanga e whakarato ana i te atahanga whakahaere. |
| `control_loras[].preprocess` |  | enum (string) | no | `None` | `canny`, `depth`, `None` | Tikanga tukatuka-mua ka whakamahia ki te atahanga kua tukuna. |
| `controlnets` |  | array of object {path, config_url, variant, control_image_url, mask_image_url, mask_threshold, conditioning_scale, start_percentage, end_percentage} | no | `[]` |  | Whirihoranga ControlNet mō te whakaputa atahanga, he ControlNet kotahi anake i tēnei wā. |
| `controlnets[].path` |  | string | yes |  |  | Wāhi taumaha ControlNet, kua tautuhia hei URL, ara rānei. |
| `controlnets[].config_url` |  | string \| null | no |  |  | URL kōwhiringa ki te kōnae config.json o ControlNet. |
| `controlnets[].variant` |  | string \| null | no |  |  | Rerekētanga kōwhiringa hei whakamahi me tētahi kī putunga Hugging Face. |
| `controlnets[].control_image_url` |  | string (image URL) | yes |  |  | URL atahanga e whakarato ana i te atahanga whakahaere. |
| `controlnets[].mask_image_url` |  | string (image URL) | no |  |  | URL kanohi e pā ana ki te atahanga whakahaere. |
| `controlnets[].mask_threshold` |  | number | no | `0.5` | 0.01 – 0.99 | Uara paepae kanohi. |
| `controlnets[].conditioning_scale` |  | number | no | `1` | 0 – 2 | Te tauine mō ngā taumaha ControlNet i mua i te hanumi ki te tauira pūtake. |
| `controlnets[].start_percentage` |  | number | no | `0` | 0 – 1 | Ōrau o ngā wāhanga katoa ka tīmata ai a ControlNet ki te whakaawe i te whakaputanga atahanga. |
| `controlnets[].end_percentage` |  | number | no | `1` | 0 – 1 | Ōrau o ngā wāhanga katoa ka mutu ai te whakaawe a ControlNet i te whakaputanga atahanga. |
| `controlnet_unions` |  | array of object {path, config_url, variant, controls} | no | `[]` |  | Whirihoranga uniana ControlNet mō te whakaputa atahanga, kei raro i te here o nāianei mō te ControlNet kotahi. |
| `controlnet_unions[].path` |  | string | yes |  |  | Wāhi taumaha ControlNet, kua tautuhia hei URL, ara rānei. |
| `controlnet_unions[].config_url` |  | string \| null | no |  |  | URL kōwhiringa ki te kōnae config.json o ControlNet. |
| `controlnet_unions[].variant` |  | string \| null | no |  |  | Rerekētanga kōwhiringa hei whakamahi me tētahi kī putunga Hugging Face. |
| `controlnet_unions[].controls` |  | array of object {control_image_url, mask_image_url, control_mode, conditioning_scale, mask_threshold, start_percentage, end_percentage} | yes |  |  | Ngā atahanga whakahaere me ngā aratau e pā ana ka tukuna ki ControlNet. |
| `controlnet_unions[].controls[].control_image_url` |  | string (image URL) | yes |  |  | URL atahanga e whakarato ana i te atahanga whakahaere. |
| `controlnet_unions[].controls[].mask_image_url` |  | string (image URL) | no |  |  | URL kanohi e pā ana ki te atahanga whakahaere. |
| `controlnet_unions[].controls[].control_mode` |  | enum (string) | yes |  | `canny`, `tile`, `depth`, `blur`, `pose`, `gray`, `low-quality` | Aratau whakahaere e whakamahia ana e Flux Controlnet Union. Ngā kōwhiringa: mā canny e ārahi mā ngā tapa; mā tile e ārahi mā ngā tāpa; mā depth e ārahi mā tētahi mahere hōhonu kirikākā; mā blur e pōuri ai te atahanga; mā pose e ārahi mā te tūnga o te atahanga; mā gray e kirikākā ai te atahanga; mā low-quality e whakaputa ai he putanga kounga-iti o te atahanga. |
| `controlnet_unions[].controls[].conditioning_scale` |  | number | no | `1` | 0 – 2 | Te tauine mō ngā taumaha ControlNet i mua i te hanumi ki te tauira pūtake. |
| `controlnet_unions[].controls[].mask_threshold` |  | number | no | `0.5` | 0.01 – 0.99 | Uara paepae kanohi. |
| `controlnet_unions[].controls[].start_percentage` |  | number | no | `0` | 0 – 1 | Ōrau o ngā wāhanga katoa ka tīmata ai a ControlNet ki te whakaawe i te whakaputanga atahanga. |
| `controlnet_unions[].controls[].end_percentage` |  | number | no | `1` | 0 – 1 | Ōrau o ngā wāhanga katoa ka mutu ai te whakaawe a ControlNet i te whakaputanga atahanga. |
| `ip_adapters` |  | array of object {path, subfolder, weight_name, image_encoder_path, image_encoder_subfolder, image_encoder_weight_name, image_url, mask_image_url, mask_threshold, scale} | no | `[]` |  | IP-Adapter ka whakamahia i te whakaputanga atahanga. |
| `ip_adapters[].path` |  | string | yes |  |  | Wāhi IP-Adapter i Hugging Face. |
| `ip_adapters[].subfolder` |  | string \| null | no |  |  | Kōpakiroto kei roto ngā taumaha ip_adapter. |
| `ip_adapters[].weight_name` |  | string \| null | no |  |  | Ingoa kōnae Safetensors mō ngā taumaha IP-Adapter. |
| `ip_adapters[].image_encoder_path` |  | string | yes |  |  | Wāhi pūwetewaehere atahanga IP-Adapter, pēnei i 'openai/clip-vit-large-patch14'. |
| `ip_adapters[].image_encoder_subfolder` |  | string \| null | no |  |  | Kōpakiroto kei roto ngā taumaha mō te pūwetewaehere atahanga. |
| `ip_adapters[].image_encoder_weight_name` |  | string \| null | no |  |  | Ingoa pūwetewaehere atahanga. |
| `ip_adapters[].image_url` |  | string (image URL) | yes |  |  | URL atahanga whakatauira ka tukuna ki IP-Adapter. |
| `ip_adapters[].mask_image_url` |  | string (image URL) \| null | no |  |  | URL kanohi e pā ana ki te atahanga whakahaere. |
| `ip_adapters[].mask_threshold` |  | number | no | `0.5` | 0.01 – 0.99 | Uara paepae kanohi. |
| `ip_adapters[].scale` |  | number | yes |  |  | Tauwehe tauine IP-Adapter. |
| `easycontrols` |  | array of object {control_method_url, scale, image_url, image_control_type} | no | `[]` |  | Ngā tāuru EasyControl ka whakamahia i te whakaputanga atahanga. |
| `easycontrols[].control_method_url` |  | string | yes |  |  | URL taumaha safetensor o te tikanga whakahaere, he tautohu tautokona rānei: `canny`, `depth`, `hedsketch`, `inpainting`, `pose`, `seg`, `subject`, `ghibli`. |
| `easycontrols[].scale` |  | number | no | `1` | 0 – 2 | Tauwehe tauine o te tikanga whakahaere. |
| `easycontrols[].image_url` |  | string (image URL) | yes |  |  | URL atahanga e whakarato ana i tētahi tāuru whakahaere. |
| `easycontrols[].image_control_type` |  | enum (string) | yes |  | `subject`, `spatial` | Aratau whakahaere atahanga; ka whakaae ki `spatial` rānei `subject`. |
| `fill_image` |  | object {fill_image_url} \| null | no |  |  | Atahanga tāuru hei ārahi i te whakaputanga, ā, ka taea te whakarato ihirangi mō ngā wāhi kanohi. |
| `fill_image.fill_image_url` |  | string (image URL) \| array of image URL | no | `[]` |  | Ngā URL atahanga hei whakakī mā te redux prompting. |
| `guidance_scale` |  | number | no | `3.5` | 0 – 20 | Te kaha ū ki te tohutohu mō te kōwhiringa atahanga, kua whakaaturia hei CFG (Classifier Free Guidance). |
| `real_cfg_scale` |  | number | no | `3.5` | 0 – 5 | Te kaha ū ki te tohutohu mō te kōwhiringa atahanga, kua whakaaturia hei CFG (Classifier Free Guidance). |
| `use_real_cfg` |  | boolean | no | `false` |  | Whakakā CFG tawhito, ka whakahohe aunoa me XLabs IP-Adapter v1. He ōrite te whanonga ārahi ki ngā tauira pēnei i SD1.5 me SDXL. |
| `use_cfg_zero` |  | boolean | no | `false` |  | Whakahohe i te tauira tīmatanga CFG-zero, kua whakaahuatia ki https://arxiv.org/abs/2503.18886. |
| `num_images` | `num_outputs` | integer | no | `1` | 1 – 10 | Tautuhia te maha o ngā atahanga hei whakaputa; ka pūmau tēnei ki te 1 ina tukuna haeretia te putanga. |
| `enable_safety_checker` |  | boolean | no | `true` |  | Te tirotiro haumaru, ka whakahoki atahanga pango hei whakakapi i ngā atahanga kua tohungia he haumaru-kore. Mā true e whakahohe te tirotiro; mā false e mono anake mō ngā pūkete whai mana, ā, ka tirotirohia ngā tono kāore he mana ahakoa te aha. |
| `reference_image_url` |  | string (image URL) | no |  |  | URL atahanga mō te ārahi Reference-Only. |
| `reference_strength` |  | number | no | `0.65` | -3 – 3 | Te whakaawe o te atahanga tohutoro i te whakaputanga reference_only; ki te kore he atahanga tohutoro, kāore he pānga o tēnei kaha. |
| `reference_start` |  | number | no | `0` | 0 – 1 | Tīmatanga o te ārahi tohutoro, hei ōrau o ngā wāhanga katoa. |
| `reference_end` |  | number | no | `1` | 0 – 1 | Mutunga o te ārahi tohutoro, hei ōrau o ngā wāhanga katoa. |
| `base_shift` |  | number | no | `0.5` | 0.01 – 5 | Nekehanga pūtake ka whakamahia ki ngā wāhanga kua whakaritea. |
| `max_shift` |  | number | no | `1.15` | 0.01 – 5 | Nekehanga mōrahi ka whakamahia ki ngā wāhanga kua whakaritea. |
| `output_format` |  | enum (string) | no | `png` | `jpeg`, `png` | Te hōputu kōnae mō te atahanga ka puta. |
| `use_beta_schedule` |  | boolean | no | `false` |  | Ka whakahaere mēnā ka whakamahia ngā beta sigmas. |
| `sigma_schedule` |  | string \| null | no |  |  | Hōtaka sigma ka whakamahia i te whakakore haruru. |
| `scheduler` |  | enum (string) | no | `euler` | `euler`, `dpmpp_2m` | Kaiwhakarite ka whakamahia i te whakakore haruru. |
| `negative_prompt` |  | string | no | `` |  | Tohutohu tōraro ka tukatukahia mā NAG hei taunoa, hei aukati i ngā āhuatanga kāore e hiahiatia ana i ngā atahanga kua whakaputaina. |
| `nag_scale` |  | number | no | `3` | ≤ 10, > 1 | Te karo tohutohu tōraro e whakahaerehia ana e te tauine NAG: mā te whakanui ka iti ake te ōrite o te atahanga kua whakaputaina ki te whakaahuatanga tōraro. |
| `nag_tau` |  | number | no | `2.5` | > 0 | Tautuhinga NAG tau mō te whakarite āhua huna; e taunakitia ana kia kaua e whakarerekē. Mā te hiki ka ngoikore te whakarite, ā, ka tūpono rerekē ohorere mai i te atahanga taketake. |
| `nag_alpha` |  | number | no | `0.25` | ≤ 1, > 0 | Mā NAG alpha e tautuhi te nui o te whakahāngai anō a te tohutohu pai i te ārahi kua whakaritea e whakakotahi ana i ngā tohutohu pai, tōraro hoki. Mā tēnei taumahatanga whakamutunga ka kaha ake te awe o te tohutohu pai i ngā tautuhinga iti, ā, ka iti ake te whakahāngai anō i ngā tautuhinga nui. |
| `nag_end` |  | number | no | `0.25` | ≤ 1, > 0 | Tapahanga NAG hei ōwehenga o ngā hipanga whakaputanga. Ka riro mā ngā pūtukatuka aro taketake o FLUX e whakahaere i muri i te whakahaeretanga o NAG mō taua ōwehenga tīmatanga. |
| `image_url` | `image` | string (image URL) | yes |  |  | URL atahanga e whakarato ana i te atahanga tīmatanga. |
| `change_map_image_url` |  | string (image URL) | yes |  |  | URL e tohu ana ki te mahere panoni. |
| `strength` |  | number | no | `0.85` | 0.01 – 1 | Te kaha diffusion rerekē, mai i te pupuri i te taketake i te 0.0 ki te hanga anō katoa i te 1.0. |

File parameters (`reference_image_url`, `image`, `change_map_image_url`) 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",
  "image": "https://content.doitong.com/images/showcase/v3/gen_fox_cartoon.jpg",
  "change_map_image_url": "https://content.doitong.com/images/showcase/v3/gen_fox_cartoon.jpg"
}
```

A fuller example:

```json
{
  "prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field",
  "image_url": "https://content.doitong.com/images/showcase/v3/gen_fox_cartoon.jpg",
  "change_map_image_url": "https://content.doitong.com/images/showcase/v3/gen_fox_cartoon.jpg"
}
```

## 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/flux-general/differential-diffusion?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",
    "image_url": "https://content.doitong.com/images/showcase/v3/gen_fox_cartoon.jpg",
    "change_map_image_url": "https://content.doitong.com/images/showcase/v3/gen_fox_cartoon.jpg"
  }'

# 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/flux-general/differential-diffusion?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",
    "image_url": "https://content.doitong.com/images/showcase/v3/gen_fox_cartoon.jpg",
    "change_map_image_url": "https://content.doitong.com/images/showcase/v3/gen_fox_cartoon.jpg"
  }),
});
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 = {
    "prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field",
    "image_url": "https://content.doitong.com/images/showcase/v3/gen_fox_cartoon.jpg",
    "change_map_image_url": "https://content.doitong.com/images/showcase/v3/gen_fox_cartoon.jpg",
}

# Run the model; wait up to 20 s for the finished result in the same call
r = requests.post(API + "/run/flux-general/differential-diffusion", 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": "flux-general/differential-diffusion",
      "input": {
        "prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field",
        "image_url": "https://content.doitong.com/images/showcase/v3/gen_fox_cartoon.jpg",
        "change_map_image_url": "https://content.doitong.com/images/showcase/v3/gen_fox_cartoon.jpg"
      },
      "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": "flux-general/differential-diffusion",
  "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": 138,
    "usd": "0.138",
    "charged": 138,
    "refunded": 0
  },
  "input": {
    "prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field",
    "image_url": "https://content.doitong.com/images/showcase/v3/gen_fox_cartoon.jpg",
    "change_map_image_url": "https://content.doitong.com/images/showcase/v3/gen_fox_cartoon.jpg"
  },
  "output": {
    "images": [
      {
        "url": "https://content.doitong.com/dev-api/2026/10/20/req_8k2m4q7x1z9c3v5b6n0p2r4t/0-output.jpeg",
        "width": 1024,
        "height": 768,
        "content_type": "image/jpeg"
      }
    ],
    "timings": {},
    "seed": 42,
    "has_nsfw_concepts": [
      false
    ],
    "prompt": "string"
  },
  "outputs": [
    {
      "type": "image",
      "url": "https://content.doitong.com/dev-api/2026/10/20/req_8k2m4q7x1z9c3v5b6n0p2r4t/0-output.jpeg",
      "content_type": "image/jpeg",
      "file_size": 1843200,
      "width": 1024,
      "height": 768,
      "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 |
|---|---|---|
| `images` | array of object {url, width, height, content_type} | Pārongo kōnae mō ngā atahanga kua whakaputaina. |
| `timings` | object |  |
| `seed` | integer | Kākano whakaputa atahanga, tae atu ki te uara i kōwhiria matapōkeretia mēnā kāore i tukuna he kākano ki te tāuru; ki te kore, ka tukurua te uara i tukuna. |
| `has_nsfw_concepts` | array of boolean | Ka tohu mēnā ka puta ngā ariā NSFW i ngā atahanga kua whakaputaina. |
| `prompt` | string | Te tohutohu e whakamahia ana i te whakaputanga atahanga. |

## Related models

- [FLUX.1 \[dev\] with Controlnets and Loras](https://doitong.com/developers/models/flux-general.md) (`flux-general`): $0.30 / image
- [FLUX.1 \[dev\] with Controlnets and Loras · Image to Image](https://doitong.com/developers/models/flux-general/image-to-image.md) (`flux-general/image-to-image`): $0.15 / image
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- [FLUX.1 Kontext \[pro\]](https://doitong.com/developers/models/flux-pro/kontext.md) (`flux-pro/kontext`): $0.04 / image
- [GPT Image 2.5 Edit](https://doitong.com/developers/models/openai/gpt-image-2.5/flare/edit.md) (`openai/gpt-image-2.5/flare/edit`): from $0.12 / image
- [Nano Banana 2 Edit](https://doitong.com/developers/models/nano-banana-2/edit.md) (`nano-banana-2/edit`): from $0.06 / image
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## Links

- HTML page: https://doitong.com/developers/models/flux-general/differential-diffusion
- 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=flux-general/differential-diffusion
- Errors: https://doitong.com/developers/docs/errors
- Model details as JSON: https://api.doitong.com/v1/models/flux-general/differential-diffusion