Wan 2.2 Text To Image Realism

Playground

WAN 2.2 delivers ultra-realistic text-to-image generation, converting prompts into photoreal images with high fidelity and detail. Ready-to-use REST inference API, best performance, no coldstarts, affordable pricing.

Features

Wan 2.2 Text-to-Image Realism

Generate photorealistic images from detailed text descriptions with Wan 2.2 Realism. This specialized model excels at creating lifelike scenes, authentic human subjects, and natural environments — perfect for when you need images that look like real photographs.

Why It Looks Great

Photorealistic focus: Optimized specifically for realistic, photograph-like outputs.
Detailed human rendering: Excels at natural skin tones, expressions, and group compositions.
Custom dimensions: Precise control over width and height for any aspect ratio.
High resolution support: Generate images up to 1280×720 and beyond.
Prompt Enhancer: Built-in tool to refine and expand your descriptions automatically.
Reproducible results: Use the seed parameter to recreate exact outputs or explore variations.

Parameters

Parameter	Required	Description
prompt	Yes	Detailed text description of the realistic image you want to generate.
size	No	Custom dimensions with separate width and height controls.
width	No	Output width in pixels (e.g., 1280).
height	No	Output height in pixels (e.g., 720).
seed	No	Random seed for reproducibility. Use -1 for random.
output_format	No	Output file format: jpeg or png. Default: jpeg.

How to Use

Write your prompt — describe the scene in detail, including people, setting, lighting, and atmosphere.
Use Prompt Enhancer (optional) — click to automatically enrich your description.
Set dimensions — adjust width and height sliders to your desired resolution.
Set seed (optional) — use -1 for random, or a specific number to reproduce results.
Choose output format — select jpeg for smaller files or png for higher quality.
Run — click the button to generate.
Download — preview and save your realistic image.

Pricing

Flat rate per image generation.

Output	Cost
Per image	$0.025

Examples

Images Generated	Total Cost
1	$0.025
10	$0.25
40	$1.00
100	$2.50

Best Use Cases

Lifestyle & Stock Photography — Generate authentic-looking lifestyle scenes and stock imagery.
Group Portraits — Create realistic multi-person compositions with natural interactions.
Environmental Scenes — Produce believable outdoor settings, gatherings, and events.
Marketing & Advertising — Generate photorealistic visuals for campaigns without photoshoots.
Concept Visualization — Visualize realistic scenarios for presentations and pitches.

Example Prompts

“A group of four women are seated around a wooden picnic table outdoors at a backyard gathering. The woman in the foreground, light-skinned and young adult, has shoulder-length light brown hair and a friendly, smiling expression. She’s wearing a white, sleeveless top.”
“Professional headshot of a middle-aged businessman in a navy suit, soft studio lighting, neutral gray background, confident expression”
“Family enjoying breakfast in a sunny modern kitchen, natural morning light through windows, warm and authentic atmosphere”
“Two colleagues having a conversation in a contemporary office space, natural poses, professional but relaxed mood”
“Street photographer capturing city life, candid moment, golden hour lighting, urban background with bokeh”

Pro Tips for Best Results

Be extremely detailed — describe physical features, clothing, expressions, and positioning.
Include lighting details — “natural sunlight”, “soft studio lighting”, “golden hour”.
Specify skin tones, ages, and distinguishing features for accurate human rendering.
Describe the environment and background to ground the scene in reality.
Use landscape dimensions (1280×720) for group scenes, portrait (720×1280) for individual shots.
The more specific your prompt, the more realistic and controlled the output.

Notes

This model is optimized for realism — for artistic or stylized outputs, consider other models.
Higher detail in prompts generally produces more accurate and realistic results.
Generation time may vary based on resolution and current queue load.
For multi-person scenes, describe each person’s position and appearance clearly.

Authentication

For authentication details, please refer to the Authentication Guide.

API Endpoints

Submit Task & Query Result


# Submit the task
curl --location --request POST "https://api.wavespeed.ai/api/v3/wavespeed-ai/wan-2.2/text-to-image-realism" \
--header "Content-Type: application/json" \
--header "Authorization: Bearer ${WAVESPEED_API_KEY}" \
--data-raw '{
    "size": "1024*1024",
    "seed": -1,
    "output_format": "jpeg",
    "enable_sync_mode": false,
    "enable_base64_output": false
}'

# Get the result
curl --location --request GET "https://api.wavespeed.ai/api/v3/predictions/${requestId}/result" \
--header "Authorization: Bearer ${WAVESPEED_API_KEY}"

Parameters

Task Submission Parameters

Request Parameters

Parameter	Type	Required	Default	Range	Description
prompt	string	Yes		-	The positive prompt for the generation.
size	string	No	1024*1024	256 ~ 1536 per dimension	The size of the generated media in pixels (width*height).
seed	integer	No	-1	-1 ~ 2147483647	The random seed to use for the generation. -1 means a random seed will be used.
output_format	string	No	jpeg	jpeg, png, webp	The format of the output image.
enable_sync_mode	boolean	No	false	-	If set to true, the function will wait for the result to be generated and uploaded before returning the response. It allows you to get the result directly in the response. This property is only available through the API.
enable_base64_output	boolean	No	false	-	If enabled, the output will be encoded into a BASE64 string instead of a URL. This property is only available through the API.

Response Parameters

Parameter	Type	Description
code	integer	HTTP status code (e.g., 200 for success)
message	string	Status message (e.g., “success”)
data.id	string	Unique identifier for the prediction, Task Id
data.model	string	Model ID used for the prediction
data.outputs	array	Array of URLs to the generated content (empty when status is not `completed`)
data.urls	object	Object containing related API endpoints
data.urls.get	string	URL to retrieve the prediction result
data.has_nsfw_contents	array	Array of boolean values indicating NSFW detection for each output
data.status	string	Status of the task: `created`, `processing`, `completed`, or `failed`
data.created_at	string	ISO timestamp of when the request was created (e.g., “2023-04-01T12:34:56.789Z”)
data.error	string	Error message (empty if no error occurred)
data.timings	object	Object containing timing details
data.timings.inference	integer	Inference time in milliseconds

Result Request Parameters

Parameter	Type	Required	Default	Description
id	string	Yes	-	Task ID

Result Response Parameters

Parameter	Type	Description
code	integer	HTTP status code (e.g., 200 for success)
message	string	Status message (e.g., “success”)
data	object	The prediction data object containing all details
data.id	string	Unique identifier for the prediction, the ID of the prediction to get
data.model	string	Model ID used for the prediction
data.outputs	string	Array of URLs to the generated content (empty when status is not completed).
data.urls	object	Object containing related API endpoints
data.urls.get	string	URL to retrieve the prediction result
data.status	string	Status of the task: `created`, `processing`, `completed`, or `failed`
data.created_at	string	ISO timestamp of when the request was created (e.g., “2023-04-01T12:34:56.789Z”)
data.error	string	Error message (empty if no error occurred)
data.timings	object	Object containing timing details
data.timings.inference	integer	Inference time in milliseconds

Wan 2.2 Text To Image LoRA Wan 2.2 Video Edit