FLUX 3 Klein Distilled Text-to-Image generates images from text prompts, with 1K or 2K output and flexible aspect ratios. Ready-to-use REST inference API, best performance, no coldstarts, affordable pricing.
Idle
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$0.01per run·~100 / $1
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A handsome young man in a perfectly tailored charcoal suit sitting on a city park bench during lunch, holding a paper bag of bread while dozens of pigeons crowd around his polished shoes. One pigeon sits confidently on his briefcase beside him. He looks down at it with a deadpan expression. Soft afternoon light, fallen leaves, newspaper pages, coffee cup, cinematic dry comedy, photorealistic detail.
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A rustic wooden kitchen table by a window with a freshly baked sourdough loaf, a ceramic bowl of ripe figs and a glass of water, warm morning sunlight casting long soft shadows, shallow depth of field, photorealistic food photography.
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A candid street photograph of a woman in her thirties with short dark hair and a mustard wool coat, walking through a quiet morning market, steam rising from a food cart behind her, soft overcast light, shallow depth of field, 35mm film look.
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A wide landscape photograph of a lone hiker standing on a ridge above a sea of clouds at sunrise, golden light on distant snow-capped peaks, crisp detail, natural colors.
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A neon sign reading OPEN above the doorway of a small noodle shop in a rainy Tokyo alley at night, reflections on the wet asphalt, a few passers-by with umbrellas, cinematic, photorealistic.
FLUX 3 Klein Distilled Text-to-Image runs the fast, production-ready FLUX 3 Klein checkpoint from Black Forest Labs (5.6B open weights). Describe the image you want and get it back in seconds.
Prompt-driven generation
Full scene captions (framing, subject, background, lighting) give the best results.
Text rendering
Clear, readable text inside generated images.
Layout control with bounding boxes
Append a JSON list of boxes on a 0 to 1000 grid to place elements; in edits, refer to the n-th reference as <ref_image_n>.
1K and 2K output
Choose 1k (~1 megapixel) or 2k (~4 megapixels) at 15 aspect ratios.
Multiple output formats
Export as jpeg, png, or webp.
Seed control
Use a fixed seed to reproduce a result, or -1 for random.
| Parameter | Required | Description |
|---|---|---|
| prompt | Yes | Text prompt describing the image to generate. |
| resolution | No | Output resolution tier: 1k or 2k. Default: 1k. |
| aspect_ratio | No | Output aspect ratio. Default: 1:1. |
| output_format | No | jpeg, png, or webp. Default: jpeg. |
| seed | No | Random seed. Use -1 for a random seed. |
1k: $0.010 per image.2k: $0.040 per image.Grab a WaveSpeedAI API key, then call POST https://api.wavespeed.ai/api/v3/wavespeed-ai/flux-3-klein-image-distilled/text-to-image with your input as JSON. The endpoint returns a prediction id. Start polling the result endpoint around every 2 seconds, increase the interval for long-running tasks, and stop on any terminal status. On completed, read output values from data.outputs. Examples for Flux 3 Klein Image Distilled Text To Image below.
set -euo pipefail
: "${WAVESPEED_API_KEY:?Set WAVESPEED_API_KEY}"
REQUEST_BODY=$(cat <<'JSON'
{
"prompt": "A cinematic shot of a city at sunset, soft golden light",
"aspect_ratio": "1:1",
"resolution": "1k",
"output_format": "jpeg"
}
JSON
)
# 1. Submit the prediction.
SUBMIT_RESPONSE=$(curl --silent --show-error --fail-with-body \
-X POST "https://api.wavespeed.ai/api/v3/wavespeed-ai/flux-3-klein-image-distilled/text-to-image" \
-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="https://api.wavespeed.ai/api/v3/predictions/$PREDICTION_ID/result"
# 2. Poll until the prediction finishes.
while true; do
RESPONSE=$(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' "$RESULT" | jq '.outputs'; break ;;
failed|cancelled|timeout|deleted) printf '%s\n' "$RESULT" | jq . >&2; exit 1 ;;
*) sleep 2 ;;
esac
doneconst submitUrl = "https://api.wavespeed.ai/api/v3/wavespeed-ai/flux-3-klein-image-distilled/text-to-image";
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 ${apiKey}`,
"Content-Type": "application/json",
},
body: JSON.stringify({
"prompt": "A cinematic shot of a city at sunset, soft golden light",
"aspect_ratio": "1:1",
"resolution": "1k",
"output_format": "jpeg"
}),
});
const task = body.data ?? body;
if (!task.id) throw new Error("Submission response did not contain a prediction id");
const resultUrl = `https://api.wavespeed.ai/api/v3/predictions/${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", "deleted"].includes(result.status)) throw new Error(JSON.stringify(result));
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",
"aspect_ratio": "1:1",
"resolution": "1k",
"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-3-klein-image-distilled/text-to-image", 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 = 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", "deleted"}:
raise RuntimeError(result)
time.sleep(2)Flux 3 Klein Image Distilled Text To Image is a WaveSpeedAI model for image generation, exposed as a REST API on WaveSpeedAI. FLUX 3 Klein Distilled Text-to-Image generates images from text prompts, with 1K or 2K output and flexible aspect ratios. 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 Python, JavaScript, and cURL examples for submitting requests and polling results. Full request/response shape is documented at https://wavespeed.ai/docs/docs-api/wavespeed-ai/flux-3-klein-image-distilled-text-to-image.
Flux 3 Klein Image Distilled Text To Image starts at $0.01 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`, `aspect_ratio`, `resolution`, `seed`, `enable_base64_output`, `enable_sync_mode`. 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-3-klein-image-distilled-text-to-image.
Sign up for a free WaveSpeedAI account to claim starter credits, copy your API key from /accesskey, then call the endpoint shown in the API tab of the playground. The playground also auto-generates a code sample in Python, JavaScript, or cURL for the parameters you've set.
Commercial usage rights depend on the model's license, set by its provider (WaveSpeedAI). Check the provider's applicable terms and WaveSpeedAI's Terms of Service before commercial use.