Minimax-image-01 Serverless API
Generate high-fidelity images from text with precise control & stunning quality with Minimax Image-01.
POST /v2/image-01 · 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 "image-01",
9 prompt="movie scene violent tsunami hitting the city, dynamic motion, realistic, cinematic, 4k",
10 aspect_ratio="1:1",
11 number_of_images=1,
12 prompt_optimizer=True,
13)
14print(result["status"]) # COMPLETED
15print(result.get("output")) # model output (e.g. media URL)
16print(result["metrics"]["inference_time"]) # server compute seconds
17
18# --- Or submit + poll manually (track request_id, control the cadence) ---
19from segmind import SegmindClient, InferenceFailed, InferenceTimeout
20
21client = SegmindClient() # reads SEGMIND_API_KEY
22payload = {
23 "prompt": "movie scene violent tsunami hitting the city, dynamic motion, realistic, cinematic, 4k",
24 "aspect_ratio": "1:1",
25 "number_of_images": 1,
26 "prompt_optimizer": True,
27}
28job = client.submit_async("image-01", **payload)
29print(job.request_id) # available immediately
30try:
31 result = job.wait(timeout=600, interval=1.0)
32except InferenceTimeout as e:
33 print("still running:", e.request_id)
34except InferenceFailed as e:
35 print("failed:", e.detail) 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 "image-01",
9 prompt="movie scene violent tsunami hitting the city, dynamic motion, realistic, cinematic, 4k",
10 aspect_ratio="1:1",
11 number_of_images=1,
12 prompt_optimizer=True,
13)
14print(result["status"]) # COMPLETED
15print(result.get("output")) # model output (e.g. media URL)
16print(result["metrics"]["inference_time"]) # server compute seconds
17
18# --- Or submit + poll manually (track request_id, control the cadence) ---
19from segmind import SegmindClient, InferenceFailed, InferenceTimeout
20
21client = SegmindClient() # reads SEGMIND_API_KEY
22payload = {
23 "prompt": "movie scene violent tsunami hitting the city, dynamic motion, realistic, cinematic, 4k",
24 "aspect_ratio": "1:1",
25 "number_of_images": 1,
26 "prompt_optimizer": True,
27}
28job = client.submit_async("image-01", **payload)
29print(job.request_id) # available immediately
30try:
31 result = job.wait(timeout=600, interval=1.0)
32except InferenceTimeout as e:
33 print("still running:", e.request_id)
34except InferenceFailed as e:
35 print("failed:", e.detail)API Endpoint
https://api.segmind.com/v1/image-01Parameters
promptrequiredstringText prompt for generation
aspect_ratiooptionalstringAspect ratio of the ouput image
"1:1""1:1""16:9""4:3""3:2""2:3""3:4""9:16""21:9"number_of_imagesoptionalintegerNumber of images to generate
1Range: 1 - 9prompt_optimizeroptionalbooleanUse prompt optimizer
trueResponse Type
Returns: Image
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
POST /v2/image-01Submit — returns request_id, status_url, response_url
- 2
GET /v2/requests/{id}/statusPoll — until COMPLETED or FAILED
- 3
GET /v2/requests/{id}Result — final response body
Status states
- 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.
Bad Request
Invalid parameters or request format
Unauthorized
Missing or invalid API key
Forbidden
Insufficient permissions
Not Found
Model or endpoint not found
Insufficient Credits
Not enough credits to process request
Rate Limited
Too many requests
Server Error
Internal server error
Bad Gateway
Service temporarily unavailable
Timeout
Request timed out