FLUX SRPO [dev] is a 12-billion-parameter flow transformer that generates high-quality, aesthetically rich images from text prompts for personal and commercial use. Ready-to-use REST inference API, best performance, no coldstarts, affordable pricing.
Idle

$0.025per run·~40 / $1

A young woman with braided hair, wearing a linen dress, picking wildflowers in a sun-drenched meadow, a wicker basket in her hand, impressionistic style, soft focus, golden hour lighting.

A cozy reading nook in a rustic cabin, a soft blanket draped over an armchair, a steaming mug of coffee on a wooden stool, morning sunlight streaming through the window, peaceful and serene atmosphere, photorealistic, warm tones.

Minimalist apartment living room in Scandinavia, clean lines, neutral color palette with a pop of green from a monstera plant, soft diffused light from a large window, Eames lounge chair, realistic 3D render, tranquil.

Epic cinematic wide shot of the Swiss Alps at sunrise, jagged snow-capped peaks breaking through a sea of low-hanging clouds, vibrant alpenglow painting the sky in hues of orange and pink, a lone eagle soaring, hyperrealistic, 8K, breathtaking.

A portrait of a pensive woman looking out a rain-streaked window at a bustling city street at night, neon signs reflecting on the glass, moody, Blade Runner aesthetic, shallow depth of field, bokeh lights.

A sprawling, mystical elven city built into giant, ancient trees, connected by glowing rope bridges, waterfalls cascading down, ethereal light, high fantasy concept art, hyper-detailed, Lord of the Rings aesthetic.

ultra realistic photo, a beautiful young woman with freckles and messy blonde hair, soft natural light filtering through a window, gentle smile, detailed skin texture, shallow depth of field, 8k, photorealistic

cozy and rustic still life, a steaming cup of coffee on a wooden table, an open book with worn pages, a lit candle casting a warm glow, autumn leaves scattered around, soft focus, warm and inviting atmosphere, hyper-detailed

cinematic film still from a romantic movie, a couple dancing in the rain on a Parisian street at night, warm glow from the streetlights, reflections on the wet cobblestone, joyful expressions, shallow depth of field, anamorphic lens flare, moody and atmospheric, photorealistic, 8k

epic landscape painting of the Scottish Highlands, a dramatic storm clearing at sunset, sunbeams breaking through dark clouds over a vast, misty valley with a serene loch, hyper-detailed, powerful and majestic, style of Albert Bierstadt, digital painting

An explosive burst of colorful powder paint captured in mid-air against a stark black background, dynamic motion, high-speed photography, abstract art, vibrant and energetic, macro details.
FLUX SRPO is a high-quality image generation model that creates stunning visuals from text descriptions. Built on the FLUX architecture with SRPO optimization, it delivers exceptional detail, composition, and artistic quality at an affordable price.
| Parameter | Required | Description |
|---|---|---|
| prompt | Yes | Text description of the image you want to generate. |
| width | No | Output width in pixels (default: 1024). |
| height | No | Output height in pixels (default: 1024). |
| strength | No | Generation strength (default: 0.8). |
| num_inference_steps | No | Quality/speed trade-off (default: 28). |
| seed | No | Set for reproducibility; -1 for random. |
| guidance_scale | No | Prompt adherence strength (default: 3.5). |
| output_format | No | Output format: jpeg or png (default: jpeg). |
| enable_base64_output | No | Return base64 string instead of URL (API only). |
| enable_sync_mode | No | Wait for result before returning response (API only). |
| Output | Price |
|---|---|
| Per image | $0.025 |
Grab a WaveSpeedAI API key, then call POST https://api.wavespeed.ai/api/v3/wavespeed-ai/flux-srpo with your input as JSON. The endpoint returns a prediction id. Start polling the result endpoint around every 2 seconds, increase the interval for long-running tasks, and stop on any terminal status. On completed, read output values from data.outputs. Examples for Flux Srpo below.
set -euo pipefail
: "${WAVESPEED_API_KEY:?Set WAVESPEED_API_KEY}"
REQUEST_BODY=$(cat <<'JSON'
{
"prompt": "A cinematic shot of a city at sunset, soft golden light",
"size": "1024*1024",
"strength": 0.8,
"num_inference_steps": 28,
"seed": -1,
"guidance_scale": 3.5,
"output_format": "jpeg"
}
JSON
)
# 1. Submit the prediction.
SUBMIT_RESPONSE=$(curl --silent --show-error --fail-with-body \
-X POST "https://api.wavespeed.ai/api/v3/wavespeed-ai/flux-srpo" \
-H "Content-Type: application/json" \
-H "Authorization: Bearer $WAVESPEED_API_KEY" \
-d "$REQUEST_BODY")
TASK=$(printf '%s' "$SUBMIT_RESPONSE" | jq 'if has("data") then .data else . end')
PREDICTION_ID=$(printf '%s' "$TASK" | jq -r '.id')
if [ -z "$PREDICTION_ID" ] || [ "$PREDICTION_ID" = "null" ]; then
printf 'Submission response did not contain a prediction id
' >&2
exit 1
fi
RESULT_URL=$(printf '%s' "$TASK" | jq -r '.urls.get // empty')
if [ -z "$RESULT_URL" ]; then
RESULT_URL="https://api.wavespeed.ai/api/v3/predictions/$PREDICTION_ID/result"
fi
# 2. Poll until the prediction finishes.
while true; do
RESPONSE=$(curl --silent --show-error --fail-with-body "$RESULT_URL" \
-H "Authorization: Bearer $WAVESPEED_API_KEY")
RESULT=$(printf '%s' "$RESPONSE" | jq 'if has("data") then .data else . end')
STATUS=$(printf '%s' "$RESULT" | jq -r '.status')
case "$STATUS" in
completed) printf '%s\n' "$RESULT" | jq '.outputs'; break ;;
failed|cancelled|timeout) printf '%s\n' "$RESULT" | jq . >&2; exit 1 ;;
created|processing) sleep 2 ;;
*) printf 'Unexpected status: %s
' "$STATUS" >&2; exit 1 ;;
esac
doneconst submitUrl = "https://api.wavespeed.ai/api/v3/wavespeed-ai/flux-srpo";
const apiKey = process.env.WAVESPEED_API_KEY;
if (!apiKey) throw new Error('Set WAVESPEED_API_KEY');
async function requestJson(url, options = {}) {
const response = await fetch(url, options);
if (!response.ok) throw new Error(await response.text());
return response.json();
}
// 1. Submit the prediction.
const body = await requestJson(submitUrl, {
method: "POST",
headers: {
"Authorization": `Bearer ${apiKey}`,
"Content-Type": "application/json",
},
body: JSON.stringify({
"prompt": "A cinematic shot of a city at sunset, soft golden light",
"size": "1024*1024",
"strength": 0.8,
"num_inference_steps": 28,
"seed": -1,
"guidance_scale": 3.5,
"output_format": "jpeg"
}),
});
const task = body.data ?? body;
if (!task.id) throw new Error("Submission response did not contain a prediction id");
const resultUrl = task.urls?.get ||
`https://api.wavespeed.ai/api/v3/predictions/${task.id}/result`;
// 2. Poll until the prediction finishes.
while (true) {
const resultBody = await requestJson(resultUrl, {
headers: { "Authorization": `Bearer ${apiKey}` },
});
const result = resultBody.data ?? resultBody;
if (result.status === "completed") {
console.log(result.outputs);
break;
}
if (["failed", "cancelled", "timeout"].includes(result.status)) throw new Error(JSON.stringify(result));
if (!["created", "processing"].includes(result.status)) throw new Error("Unexpected status: " + result.status);
await new Promise(resolve => setTimeout(resolve, 2000));
}import json
import os
import time
from urllib.request import Request, urlopen
api_key = os.environ["WAVESPEED_API_KEY"]
headers = {"Authorization": f"Bearer {api_key}", "Content-Type": "application/json"}
payload = {
"prompt": "A cinematic shot of a city at sunset, soft golden light",
"size": "1024*1024",
"strength": 0.8,
"num_inference_steps": 28,
"seed": -1,
"guidance_scale": 3.5,
"output_format": "jpeg"
}
def request_json(url, data=None):
request = Request(url, data=data, headers=headers, method="POST" if data else "GET")
with urlopen(request) as response:
return json.load(response)
# 1. Submit the prediction.
body = request_json("https://api.wavespeed.ai/api/v3/wavespeed-ai/flux-srpo", json.dumps(payload).encode())
task = body.get("data", body)
if not task.get("id"):
raise RuntimeError("Submission response did not contain a prediction id")
result_url = task.get("urls", {}).get("get") or f"https://api.wavespeed.ai/api/v3/predictions/{task['id']}/result"
# 2. Poll until the prediction finishes.
while True:
result_body = request_json(result_url)
result = result_body.get("data", result_body)
status = result.get("status")
if status == "completed":
print(result.get("outputs", []))
break
if status in {"failed", "cancelled", "timeout"}:
raise RuntimeError(result)
if status not in {"created", "processing"}:
raise RuntimeError(f"Unexpected status: {status}")
time.sleep(2)Flux Srpo is a WaveSpeedAI model for image generation, exposed as a REST API on WaveSpeedAI. FLUX SRPO [dev] is a 12-billion-parameter flow transformer that generates high-quality, aesthetically rich images from text prompts for personal and commercial use. Ready-to-use REST inference API, best performance, no coldstarts, affordable pricing. You can call it programmatically or try it from the playground above.
POST your input parameters to the model's REST endpoint (shown in the API tab of this playground) with your WaveSpeedAI API key in the Authorization header. Submission returns a prediction ID. Poll the result endpoint starting around every 2 seconds, increase the interval for long-running tasks, and stop on any terminal status. The playground generates production-oriented Python, JavaScript, and cURL examples with timeouts, transient-error handling, and safe GET retries. Full request/response shape is documented at https://wavespeed.ai/docs/docs-api/wavespeed-ai/flux-srpo.
Flux Srpo starts at $0.025 per run. That figure is the base price — the final charge scales with the parameters you set in the form (output size, length, count, references, or whatever knobs this model exposes), so a higher-quality or larger output costs more than a minimal one. The exact cost for your current input is shown live next to the Generate button before you submit, and the actual per-call charge is recorded on the prediction afterwards.
Key inputs: `prompt`, `size`, `seed`, `guidance_scale`, `num_inference_steps`, `enable_base64_output`. The full JSON schema (types, defaults, allowed values) is rendered above the Generate button and mirrored in the API reference at https://wavespeed.ai/docs/docs-api/wavespeed-ai/flux-srpo.
Median end-to-end generation time on WaveSpeedAI is around 83 seconds per request, based on recent successful runs. Queue time varies with global demand; live status is visible in the prediction record.
Commercial usage rights depend on the model's license, set by its provider (WaveSpeedAI). The license summary appears on the model card above; see WaveSpeedAI's Terms of Service for platform-level conditions.