Stable Diffusion 3 Large Text to Image Serverless API

Stable Diffusion is a type of latent diffusion model that can generate images from text. It was created by a team of researchers and engineers from CompVis, Stability AI, and LAION. Stable Diffusion v2 is a specific version of the model architecture. It utilizes a downsampling-factor 8 autoencoder with an 865M UNet and OpenCLIP ViT-H/14 text encoder for the diffusion model. When using the SD 2-v model, it produces 768x768 px images. It uses the penultimate text embeddings from a CLIP ViT-H/14 text encoder to condition the generation process.

~9.59s
POST /v2/stable-diffusion-3-large-txt2img · submit + poll
 1# pip install "segmind>=1.1.0"
 2# export SEGMIND_API_KEY="YOUR_API_KEY"
 3import segmind
 4
 5# Async (v2): submit to the queue and block until COMPLETED.
 6# run() returns the final result dict (600s deadline, 1.0s poll by default).
 7result = segmind.run(
 8    "stable-diffusion-3-large-txt2img",
 9    prompt="A whimsical and high-resolution highly realistic image of a panda in a vintage cosmonaut suit. The panda is holding a sign that reads 'I love flying to the moon!' in playful lettering. The panda's helmet has a small propeller on top and a Indian flag patch, adding to the cosmic vibe. The background features a retro-styled spaceship with rockets and stars, giving the impression of a thrilling journey through space",
10    mode="text-to-image",
11    aspect_ratio="1:1",
12    output_format="jpeg",
13    base64=False,
14    negative_prompt="ugly, blurry, bad anatomy, blurred, watermark, grainy, signature, cut off, draft",
15)
16print(result["status"])                      # COMPLETED
17print(result.get("output"))                  # model output (e.g. media URL)
18print(result["metrics"]["inference_time"])   # server compute seconds
19
20# --- Or submit + poll manually (track request_id, control the cadence) ---
21from segmind import SegmindClient, InferenceFailed, InferenceTimeout
22
23client = SegmindClient()                      # reads SEGMIND_API_KEY
24payload = {
25    "prompt": "A whimsical and high-resolution highly realistic image of a panda in a vintage cosmonaut suit. The panda is holding a sign that reads 'I love flying to the moon!' in playful lettering. The panda's helmet has a small propeller on top and a Indian flag patch, adding to the cosmic vibe. The background features a retro-styled spaceship with rockets and stars, giving the impression of a thrilling journey through space",
26    "mode": "text-to-image",
27    "aspect_ratio": "1:1",
28    "output_format": "jpeg",
29    "base64": False,
30    "negative_prompt": "ugly, blurry, bad anatomy, blurred, watermark, grainy, signature, cut off, draft",
31}
32job = client.submit_async("stable-diffusion-3-large-txt2img", **payload)
33print(job.request_id)                         # available immediately
34try:
35    result = job.wait(timeout=600, interval=1.0)
36except InferenceTimeout as e:
37    print("still running:", e.request_id)
38except InferenceFailed as e:
39    print("failed:", e.detail)

API Endpoint

POSThttps://api.segmind.com/v1/stable-diffusion-3-large-txt2img

Parameters

aspect_ratiooptional
string

aspect_ratio

Default: "1:1"
Allowed values :
"16:9""1:1""21:9""2:3""3:2""4:5""5:4""9:16""9:21"
base64optional
boolean

Base64 encoding of the output image.

Default: false
modeoptional
string

Type of mode.

Default: "text-to-image"
Allowed values :
"text-to-image""image-to-image"
negative_promptoptional
string

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

Default: ""
output_formatoptional
string

Output format.

Default: "jpeg"
Allowed values :
"jpeg""png"
promptoptional
string

Prompt to render

Response Type

Returns: Text/JSON

Asynchronous requests (v2)

Use Async for video, long-running (>~60s), or high-concurrency workloads; Sync is simplest for fast image & LLM calls. Async submits a request and you poll it to completion.

  1. 1
    POST /v2/stable-diffusion-3-large-txt2img

    Submitreturns request_id, status_url, response_url

  2. 2
    GET /v2/requests/{id}/status

    Polluntil COMPLETED or FAILED

  3. 3
    GET /v2/requests/{id}

    Resultfinal response body

Status states

QUEUEDAccepted, waiting for a worker
PROCESSINGRunning on a worker
COMPLETEDDone — result body is ready
FAILEDErrored (incl. content/RAI blocks)
  • A FAILED request is served as HTTP 422 — the body still carries the error detail.
  • An unknown or expired request_id returns HTTP 404.
  • Results are retained for 1 hour, then expire.
  • Content / RAI blocks surface as FAILED, not a separate state.
  • Track completion by polling the status endpoint.

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