SSD-1B

The Segmind Stable Diffusion Model (SSD-1B) is a distilled 50% smaller version of the Stable Diffusion XL (SDXL), offering a 60% speedup while maintaining high-quality text-to-image generation capabilities. It has been trained on diverse datasets, including Grit and Midjourney scrape data, to enhance its ability to create a wide range of visual content based on textual prompts.

~2.79s

~$0.004

Playground API

Pricing

~2.79s

~$0.004

 1import requests
 2import json
 3
 4url = "https://api.segmind.com/v1/ssd-1b"
 5headers = {
 6    "x-api-key": "YOUR_API_KEY",
 7    "Content-Type": "application/json"
 8}
 9
10data = {
11    "prompt": "with smoke, half ice and half fire and ultra realistic in detail.wolf, typography, dark fantasy, wildlife photography, vibrant, cinematic and on a black background",
12    "negative_prompt": "scary, cartoon, painting",
13    "samples": 1,
14    "scheduler": "UniPC",
15    "num_inference_steps": 25,
16    "guidance_scale": 9,
17    "seed": 36446545871,
18    "img_width": 1024,
19    "img_height": 1024,
20    "base64": false
21}
22
23response = requests.post(url, headers=headers, json=data)
24
25if response.status_code == 200:
26    result = response.json()
27    print(json.dumps(result, indent=2))
28else:
29    print(f"Error: {response.status_code}")
30    print(response.text)

 1import requests
 2import json
 3
 4url = "https://api.segmind.com/v1/ssd-1b"
 5headers = {
 6    "x-api-key": "YOUR_API_KEY",
 7    "Content-Type": "application/json"
 8}
 9
10data = {
11    "prompt": "with smoke, half ice and half fire and ultra realistic in detail.wolf, typography, dark fantasy, wildlife photography, vibrant, cinematic and on a black background",
12    "negative_prompt": "scary, cartoon, painting",
13    "samples": 1,
14    "scheduler": "UniPC",
15    "num_inference_steps": 25,
16    "guidance_scale": 9,
17    "seed": 36446545871,
18    "img_width": 1024,
19    "img_height": 1024,
20    "base64": false
21}
22
23response = requests.post(url, headers=headers, json=data)
24
25if response.status_code == 200:
26    result = response.json()
27    print(json.dumps(result, indent=2))
28else:
29    print(f"Error: {response.status_code}")
30    print(response.text)

API Endpoint

POSThttps://api.segmind.com/v1/ssd-1b

Parameters

promptrequired

string

Prompt to render

base64optional

boolean

Base64 encoding of the output image.

Default: false

guidance_scaleoptional

number

Scale for classifier-free guidance

Default: 7.5Range: 1 - 25

img_heightoptional

integer

Can only be 1024 for SDXL

Default: 1024

Allowed values :

1024

img_widthoptional

integer

Can only be 1024 for SDXL

Default: 1024

Allowed values :

1024

negative_promptoptional

string

Prompts to exclude, eg. 'bad anatomy, bad hands, missing fingers'

num_inference_stepsoptional

integer

Number of denoising steps.

Default: 25Range: 20 - 100

samplesoptional

integer

Number of samples to generate.

Default: 1Range: 1 - 4

scheduleroptional

string

Type of scheduler.

Default: "DPM2 Karras"

Allowed values (12 total):

"DDIM""DPM Multi""DPM Single""Euler a""Euler""Heun""DPM2 a Karras""DPM2 Karras""LMS""PNDM"+2 more

seedoptional

integer

Seed for image generation.

Default: -1Range: -1 - 999999999999999

Response Type

Returns: Text/JSON

Common Error Codes

The API returns standard HTTP status codes. Detailed error messages are provided in the response body.

400

Bad Request

Invalid parameters or request format

401

Unauthorized

Missing or invalid API key

403

Forbidden

Insufficient permissions

404

Not Found

Model or endpoint not found

406

Insufficient Credits

Not enough credits to process request

429

Rate Limited

Too many requests

500

Server Error

Internal server error

502

Bad Gateway

Service temporarily unavailable

504

Timeout

Request timed out