ArchDiffusion v4.4-Fast

ArchDiffusion v4.4-Fast is a lightweight, fast, and cost-effective AI rendering API for architectural visualization.

How it works: v4.4-Fast takes your source image and prompt, processes it through our fast rendering engine, and returns a transformed architectural visualization. It's designed for speed and simplicity with minimal configuration.

v4.4-Fast vs v4.4-Ultra:

• Faster processing: Optimized for quick turnaround at 1K resolution
• Lower cost: Only 1 credit per generation (vs 3 credits for v4.4-Ultra)
• Simpler API: Fewer parameters to configure (up to 3 reference images)
• Expert types: Supports all 6 expert modes (exterior, interior, masterplan, landscape, plan, product)

Credit Cost: 1 credit per generation

Endpoint

HTTP Method

POST https://api.mnmlai.dev/v1/archDiffusion-v44-lite

Request

Send a POST request with multipart/form-data containing your source image and design parameters. The API processes images asynchronously, returning a request ID for status tracking.

Parameters

Parameter	Type	Default	Description
`image`Required	File	-	Source architectural image (JPEG, PNG, WebP). Max 15MB, min 1KB
`prompt`Required	String	-	Description of desired transformation (max 2000 characters)
`expert_name`	String	"exterior"	Expert mode: "exterior", "interior", "masterplan", "landscape", "plan", "product"
`output_format`	String	"png"	Output image format: "png", "jpeg", "webp"

Expert Types

exterior: Building exteriors

interior: Interior spaces

masterplan: Site plans & urban

landscape: Outdoor landscapes

plan: Floor plans

product: Product renders

Design Parameters (Optional)

These optional form fields control the rendered scene. They mirror the styling controls of the mnml studio app, and the defaults below are identical to the studio app's defaults — so omitting a field yields the same result the web app produces with its default settings. Send each as a plain form field alongside image and prompt.

Important encoding notes

• Field names are unprefixed (e.g. camera_angle, not v42_camera_angle).
• Booleans (annotation, show_dimensions) use the strings "true" / "false".
• Only the fields relevant to the chosen expert_name are applied; others are ignored.
• render_style does not accept "auto" (use an explicit style); masterplan render style has no "auto", and plan drawing_style has no "realistic" — pick a listed value.

Common (all expert types)

Parameter	Default	Options / Notes
`render_style`	photoreal	raw, photoreal, cgi_render, cad, freehand_sketch, clay_model, illustration, watercolor
`geometry`	precise	precise, creative
`view_mode`	auto	scene framing mode
`camera_angle`	auto	expert-specific angle options
`camera_direction`	front	front, left, right, back, etc.
`annotation`	false	"true" / "false"
`show_dimensions`	false	"true" / "false"
`seed`	random	integer 0–1000000 (note: not forwarded to the model; output is not deterministic)
`reference_image_1..3`	–	up to 3 optional reference image files

expert_name = "exterior"

`site_context`	auto
`greenery`	some
`vehicles`	few
`people`	few
`street_props`	off
`motion`	subtle
`time_of_day`	auto
`weather`	clear
`ground_wetness`	dry

expert_name = "interior"

`room_type`	auto
`room_style`	auto
`furnishing_level`	auto
`indoor_plants`	auto
`interior_accessories`	off
`lighting_mode`	auto
`floor_finish`	auto
`people`	auto
`ambience`	auto

expert_name = "masterplan"

`plan_mode`	3d
`camera_angle`	auto
`greenery`	moderate
`vehicles`	few
`people`	few
`urban_density`	medium
`development_type`	auto
`water_features`	none
`time_of_day`	auto
`weather`	clear

expert_name = "landscape"

`landscape_style`	modern
`camera_angle`	auto
`vegetation`	moderate
`water_features`	none
`hardscape`	pathways
`outdoor_furniture`	minimal
`landscape_lighting`	none
`people`	few
`time_of_day`	auto
`weather`	clear
`ground_wetness`	dry

expert_name = "product"

`product_category`	furniture
`camera_angle`	auto
`background`	white
`product_lighting`	soft
`material_finish`	auto
`shadow_style`	contact

expert_name = "plan"

`plan_view_mode`	2d
`drawing_style`	architectural
`color_mode`	colored
`furniture_2d`	outline
`plan_annotations`	off
`wall_style`	filled
`view_type_3d`	isometric
`ceiling`	hide
`room_style`	auto
`furnishing_3d`	moderate
`lighting_3d`	natural
`ambience_3d`	day

Response

The API processes your request asynchronously and immediately returns a response containing a unique request ID. Use this ID with the Status Check endpoint to monitor processing progress and retrieve the final generated image.

Success Response (200 OK)

{
  "status": "success",
  "id": "vysqf2nr0drmc0ctqx5tkdse48",
  "prompt": "Modern building with glass facade",
  "expert_name": "exterior",
  "parameters": {
    "renderStyle": "photoreal",
    "geometry": "precise",
    "viewMode": "auto",
    "annotation": false,
    "showDimensions": false,
    "referenceImageCount": 0,
    "thinkingLevel": "off"
  },
  "credits": 99
}

Code Examples

1. Basic Exterior Rendering (cURL)

curl -X POST https://api.mnmlai.dev/v1/archDiffusion-v44-lite \
  -H "Accept: application/json" \
  -H "Authorization: Bearer YOUR_API_KEY" \
  -H "Content-Type: multipart/form-data" \
  -F "image=@/path/to/building.jpg" \
  -F "prompt=Modern commercial building with glass facade" \
  -F "expert_name=exterior"

2. Interior Rendering

curl -X POST https://api.mnmlai.dev/v1/archDiffusion-v44-lite \
  -H "Accept: application/json" \
  -H "Authorization: Bearer YOUR_API_KEY" \
  -H "Content-Type: multipart/form-data" \
  -F "image=@/path/to/room.jpg" \
  -F "prompt=Luxury modern living room with natural lighting" \
  -F "expert_name=interior" \
  -F "output_format=jpeg"

3. Node.js Implementation

const FormData = require('form-data');
const fs = require('fs');
const axios = require('axios');

const form = new FormData();
form.append('image', fs.createReadStream('building.jpg'));
form.append('prompt', 'Modern residential building with landscaping');
form.append('expert_name', 'exterior');
form.append('output_format', 'png');

const response = await axios.post(
  'https://api.mnmlai.dev/v1/archDiffusion-v44-lite',
  form,
  {
    headers: {
      'Accept': 'application/json',
      'Authorization': 'Bearer YOUR_API_KEY',
      ...form.getHeaders()
    }
  }
);

console.log('Request ID:', response.data.id);
console.log('Remaining credits:', response.data.credits);

4. Python Implementation

import requests

url = 'https://api.mnmlai.dev/v1/archDiffusion-v44-lite'

files = {
    'image': open('building.jpg', 'rb')
}

data = {
    'prompt': 'Modern office building with green terrace',
    'expert_name': 'exterior',
    'output_format': 'png'
}

headers = {
    'Accept': 'application/json',
    'Authorization': 'Bearer YOUR_API_KEY'
}

response = requests.post(url, headers=headers, files=files, data=data)
result = response.json()

print(f"Request ID: {result['id']}")
print(f"Remaining credits: {result['credits']}")

Checking Processing Status

Status Check Endpoint

GET https://api.mnmlai.dev/v1/status/{id}

Processing Time: Typically 15-30 seconds (faster than v4.4-Ultra). Poll the status endpoint every 3-5 seconds until the status becomes "succeeded" or "failed".

Best Practices

Image Guidelines

Use high-quality source images (1024px or larger recommended)
Supported formats: JPEG, PNG, WebP
File size: 1KB - 15MB per image
Outputs are rendered at 1K resolution for fast turnaround

When to Use v4.4-Fast vs v4.4-Ultra

Use v4.4-Fast: Quick iterations, prototyping, budget-conscious projects, simpler transformations
Use v4.4-Ultra: Final presentations, 2K output, detailed control over environmental parameters, up to 4 reference images, complex styling

Prompt Tips

Be descriptive about materials, lighting, and atmosphere in your prompt
Include style references (e.g., "modern minimalist", "industrial loft")
Specify time of day or weather conditions in the prompt for desired effects

Error Handling

Common Error Responses

// 400 Bad Request - Missing image
{
  "status": "error",
  "code": "MISSING_IMAGE",
  "message": "Image file is required"
}

// 400 Bad Request - Missing prompt
{
  "status": "error",
  "code": "MISSING_PROMPT",
  "message": "Prompt is required"
}

// 400 Bad Request - Insufficient credits
{
  "status": "error",
  "code": "NO_CREDITS",
  "message": "You do not have enough credits to use this feature. This API requires 1 credit.",
  "details": { "credits": 0, "required": 1 }
}

// 400 Bad Request - Image too large
{
  "status": "error",
  "code": "IMAGE_TOO_LARGE",
  "message": "Image file is too large",
  "details": { "size": 20000000, "maxSize": 15728640 }
}

Next Steps

ArchDiffusion v4.4-Ultra Status Check