Flux Dev Finetuned Serverless API
Flux is a 12 billion parameter rectified flow transformer capable of generating images from text descriptions
POST /v2/flux-dev-finetuned · 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 "flux-dev-finetuned",
9 prompt="TOK TOK",
10 steps=25,
11 seed=6652105,
12 scheduler="simple",
13 sampler_name="euler",
14 aspect_ratio="1:1",
15 lora_strength=1,
16 hardware="cost",
17)
18print(result["status"]) # COMPLETED
19print(result.get("output")) # model output (e.g. media URL)
20print(result["metrics"]["inference_time"]) # server compute seconds
21
22# --- Or submit + poll manually (track request_id, control the cadence) ---
23from segmind import SegmindClient, InferenceFailed, InferenceTimeout
24
25client = SegmindClient() # reads SEGMIND_API_KEY
26payload = {
27 "prompt": "TOK TOK",
28 "steps": 25,
29 "seed": 6652105,
30 "scheduler": "simple",
31 "sampler_name": "euler",
32 "aspect_ratio": "1:1",
33 "lora_strength": 1,
34 "hardware": "cost",
35}
36job = client.submit_async("flux-dev-finetuned", **payload)
37print(job.request_id) # available immediately
38try:
39 result = job.wait(timeout=600, interval=1.0)
40except InferenceTimeout as e:
41 print("still running:", e.request_id)
42except InferenceFailed as e:
43 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 "flux-dev-finetuned",
9 prompt="TOK TOK",
10 steps=25,
11 seed=6652105,
12 scheduler="simple",
13 sampler_name="euler",
14 aspect_ratio="1:1",
15 lora_strength=1,
16 hardware="cost",
17)
18print(result["status"]) # COMPLETED
19print(result.get("output")) # model output (e.g. media URL)
20print(result["metrics"]["inference_time"]) # server compute seconds
21
22# --- Or submit + poll manually (track request_id, control the cadence) ---
23from segmind import SegmindClient, InferenceFailed, InferenceTimeout
24
25client = SegmindClient() # reads SEGMIND_API_KEY
26payload = {
27 "prompt": "TOK TOK",
28 "steps": 25,
29 "seed": 6652105,
30 "scheduler": "simple",
31 "sampler_name": "euler",
32 "aspect_ratio": "1:1",
33 "lora_strength": 1,
34 "hardware": "cost",
35}
36job = client.submit_async("flux-dev-finetuned", **payload)
37print(job.request_id) # available immediately
38try:
39 result = job.wait(timeout=600, interval=1.0)
40except InferenceTimeout as e:
41 print("still running:", e.request_id)
42except InferenceFailed as e:
43 print("failed:", e.detail)API Endpoint
https://api.segmind.com/v1/flux-dev-finetunedParameters
aspect_ratiorequiredstringAspect ratio for the generated image
"1:1""1:1""2:3""3:4""5:8""9:16""9:19""9:21""3:2""4:3""8:5"+3 morefinetune_idrequiredstringID of the fine-tuned model you want to use.
"my-finetune-id"lora_strengthrequirednumberStrength of the LoRA (Low-Rank Adaptation) for fine-tuning
1Range: -10 - 10promptrequiredstringText prompt for generating the image
"TOK TOK"sampler_namerequiredstringSampler type for image generation
"euler""euler""euler_pp""euler_ancestral""euler_ancestral_pp""heun""heunpp2""dpm_2""dpm_2_ancestral""lms""dpm_fast"+16 moreschedulerrequiredstringScheduler type for image generation
"simple""normal""karras""exponential""sgm_uniform""simple""ddim_uniform""beta"seedrequiredintegerSeed for random number generation
6652105stepsrequiredintegerNumber of steps for generating the image
25Range: 1 - 100hardwareoptionalstringThe hardware to use. Does not affect quality, only latency and cost
"cost""fast""cost"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
POST /v2/flux-dev-finetunedSubmit — 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