FLUX 3 Klein Base Image Edit edits and composes images from up to 3 reference images and a text prompt, with 1K or 2K output. Ready-to-use REST inference API, best performance, no coldstarts, affordable pricing.
Idle
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$0.045per run·~22 / $1
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Transform the flour inside the open sack into a tiny snow-covered mountain range with miniature peaks, valleys, pine trees, and a narrow climbing trail, while keeping the sack itself unchanged. Preserve the baker’s exact identity, pose, clothing, flour sack, bakery environment, counter, and lighting. The miniature landscape should still visually read as fine flour and remain physically contained inside the bag. Whimsical photorealistic food surrealism, highly detailed.
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Change the denim jacket to a dark green wool overcoat. Keep the man, his pose, the cafe and the lighting exactly the same.
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Turn it into a snowy winter morning: light snow falling and settled on the cobblestones and the bicycle seat. Keep the bicycle, the wall and the framing the same.
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Turn the scene into a rainy evening: warm lamps switched on, dusk light through the window with raindrops on the glass. Keep the furniture and layout unchanged.
FLUX 3 Klein Base Image Edit runs the full, non-distilled FLUX 3 Klein checkpoint for maximum fidelity (slower and priced higher than Distilled) from Black Forest Labs (5.6B open weights). Edit existing images, or combine up to 3 reference images, with a natural-language instruction.
Reference-guided editing
Pass 1 to 3 reference images; the first image sets the output shape unless aspect_ratio is given.
Multi-reference composition
Combine subjects and scenes from several images into one result.
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 desired edit. |
| images | Yes | Reference image URLs. Supports between 1 and 3 images. |
| resolution | No | Output resolution tier: 1k or 2k. Default: 1k. |
| aspect_ratio | No | Output aspect ratio. Default: follows the first reference image. |
| output_format | No | jpeg, png, or webp. Default: jpeg. |
| seed | No | Random seed. Use -1 for a random seed. |
1k: $0.045 with one reference image, plus $0.025 for each additional reference image.2k: $0.180 with one reference image, plus $0.050 for each additional reference image.1 to 3 image URLs in images.Grab a WaveSpeedAI API key, then call POST https://api.wavespeed.ai/api/v3/wavespeed-ai/flux-3-klein-image-base/edit with your input as JSON. The endpoint returns a prediction id. Start polling the result endpoint around every 2 seconds, increase the interval for long-running tasks, and stop on any terminal status. On completed, read output values from data.outputs. Examples for Flux 3 Klein Image Base Edit below.
set -euo pipefail
: "${WAVESPEED_API_KEY:?Set WAVESPEED_API_KEY}"
REQUEST_BODY=$(cat <<'JSON'
{
"prompt": "A cinematic shot of a city at sunset, soft golden light",
"images": [
"https://interactive-examples.mdn.mozilla.net/media/cc0-images/painted-hand-298-332.jpg"
],
"aspect_ratio": "1:1",
"resolution": "1k",
"output_format": "jpeg"
}
JSON
)
# 1. Submit the prediction.
SUBMIT_RESPONSE=$(curl --silent --show-error --fail-with-body \
-X POST "https://api.wavespeed.ai/api/v3/wavespeed-ai/flux-3-klein-image-base/edit" \
-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-base/edit";
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 ${apiKey}`,
"Content-Type": "application/json",
},
body: JSON.stringify({
"prompt": "A cinematic shot of a city at sunset, soft golden light",
"images": [
"https://interactive-examples.mdn.mozilla.net/media/cc0-images/painted-hand-298-332.jpg"
],
"aspect_ratio": "1:1",
"resolution": "1k",
"output_format": "jpeg"
}),
});
const task = body.data ?? body;
if (!task.id) throw new Error("Submission response did not contain a prediction id");
const resultUrl = `https://api.wavespeed.ai/api/v3/predictions/${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",
"images": [
"https://interactive-examples.mdn.mozilla.net/media/cc0-images/painted-hand-298-332.jpg"
],
"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-base/edit", 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 Base Edit is a WaveSpeedAI model for image editing, exposed as a REST API on WaveSpeedAI. FLUX 3 Klein Base Image Edit edits and composes images from up to 3 reference images and a text prompt, with 1K or 2K output. 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-base-edit.
Flux 3 Klein Image Base Edit starts at $0.045 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`, `images`, `aspect_ratio`, `resolution`, `seed`, `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-3-klein-image-base-edit.
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.