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wavespeed-ai/flux-3-klein-image-base/edit-lora

FLUX 3 Klein Base Image Edit LoRA edits and composes images from up to 3 reference images and a text prompt with up to 3 custom LoRA weights, with 1K or 2K output. Ready-to-use REST inference API, best performance, no coldstarts, affordable pricing.

Image Editing
Input

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Idle

Transform the headphones into an intricate luxury mechanical design with exposed brass micro-gears, brushed titanium ear cups, transparent side panels, fine engraved patterns, and subtle amber internal light.
Preserve the woman’s exact face, hairstyle, pose, hands, studio environment, camera angle, and headphone proportions.
Keep the headphones functional and realistic rather than oversized or fantastical. Premium industrial design, detailed material separation, cinematic product realism.

$0.05per run·~20 / $1

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ExamplesView all

Transform the headphones into an intricate luxury mechanical design with exposed brass micro-gears, brushed titanium ear cups, transparent side panels, fine engraved patterns, and subtle amber internal light.
Preserve the woman’s exact face, hairstyle, pose, hands, studio environment, camera angle, and headphone proportions.
Keep the headphones functional and realistic rather than oversized or fantastical. Premium industrial design, detailed material separation, cinematic product realism.

Transform the headphones into an intricate luxury mechanical design with exposed brass micro-gears, brushed titanium ear cups, transparent side panels, fine engraved patterns, and subtle amber internal light. Preserve the woman’s exact face, hairstyle, pose, hands, studio environment, camera angle, and headphone proportions. Keep the headphones functional and realistic rather than oversized or fantastical. Premium industrial design, detailed material separation, cinematic product realism.

Change the denim jacket to a dark green wool overcoat. Keep the man, his pose, the cafe and the lighting exactly the same.

Change the denim jacket to a dark green wool overcoat. Keep the man, his pose, the cafe and the lighting exactly the same.

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.

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.

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.

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.

Related Models

README

FLUX 3 Klein Base Image Edit LoRA

FLUX 3 Klein Base Image Edit LoRA 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. Apply up to 3 custom LoRA weights in the same request.

Why Choose This?

  • 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.

  • LoRA support
    Apply up to 3 LoRAs, each as {path, scale}.

  • 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.

Parameters

ParameterRequiredDescription
promptYesText prompt describing the desired edit.
imagesYesReference image URLs. Supports between 1 and 3 images.
lorasNoUp to 3 LoRA objects. Each item uses {path, scale}.
resolutionNoOutput resolution tier: 1k or 2k. Default: 1k.
aspect_ratioNoOutput aspect ratio. Default: follows the first reference image.
output_formatNojpeg, png, or webp. Default: jpeg.
seedNoRandom seed. Use -1 for a random seed.

Pricing

  • 1k: $0.050 with one reference image, plus $0.025 for each additional reference image.
  • 2k: $0.185 with one reference image, plus $0.050 for each additional reference image.

How to Use

  1. Write a prompt — Describe the subject, composition, background, lighting, and style in full sentences.
  2. Add reference images — Provide 1 to 3 image URLs in images.
  3. Add LoRAs (optional) — Up to 3, each with its own scale.
  4. Choose resolution and aspect ratio (optional).
  5. Submit — Retrieve the finished image from the result.
Note:This website uses AI models provided by third parties. Documentation prices are for reference and may be outdated. The Generate button shows an estimate; the final task charge prevails.

Flux 3 Klein Image Base Edit Lora API — Quick start

Grab a WaveSpeedAI API key, then call POST https://api.wavespeed.ai/api/v3/wavespeed-ai/flux-3-klein-image-base/edit-lora 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 Lora below.

HTTP example
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-lora" \
  -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
done
Node.js example
const submitUrl = "https://api.wavespeed.ai/api/v3/wavespeed-ai/flux-3-klein-image-base/edit-lora";
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));
}
Python example
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-lora", 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 Lora API — Frequently asked questions

What is the Flux 3 Klein Image Base Edit Lora API?

Flux 3 Klein Image Base Edit Lora is a WaveSpeedAI model for image editing, exposed as a REST API on WaveSpeedAI. FLUX 3 Klein Base Image Edit LoRA edits and composes images from up to 3 reference images and a text prompt with up to 3 custom LoRA weights, 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.

How do I call the Flux 3 Klein Image Base Edit Lora API?

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-lora.

How much does Flux 3 Klein Image Base Edit Lora cost per run?

Flux 3 Klein Image Base Edit Lora starts at $0.05 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.

What inputs does Flux 3 Klein Image Base Edit Lora accept?

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-lora.

How do I get started with the Flux 3 Klein Image Base Edit Lora API?

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.

Can I use Flux 3 Klein Image Base Edit Lora outputs commercially?

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.

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