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Flux 2 Klein Base 4B Text to Image | High-Quality Text-to-Image API

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FLUX.2 [klein] Base 4B is a compact 4-billion-parameter text-to-image model that delivers fast generation with quality results. Ready-to-use REST inference API, best performance, no cold starts, affordable pricing.

text-to-image
Input

Idle

Create a vintage vector travel poster of a quiet coastal town at sunset, lighthouse on a cliff, small fishing boats, rolling ocean waves, warm retro color palette, bold simplified shapes, screen-print poster style, crisp SVG edges, no text

$0.01per run·~100 / $1

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ExamplesView all

Create a vintage vector travel poster of a quiet coastal town at sunset, lighthouse on a cliff, small fishing boats, rolling ocean waves, warm retro color palette, bold simplified shapes, screen-print poster style, crisp SVG edges, no text

Create a vintage vector travel poster of a quiet coastal town at sunset, lighthouse on a cliff, small fishing boats, rolling ocean waves, warm retro color palette, bold simplified shapes, screen-print poster style, crisp SVG edges, no text

Create a mystical vector tarot card illustration of a moonlit garden, crescent moon, two hands holding a glowing key, stars, vines, symmetrical composition, ornate border, flat vector shapes, elegant gold and deep navy palette, no text

Create a mystical vector tarot card illustration of a moonlit garden, crescent moon, two hands holding a glowing key, stars, vines, symmetrical composition, ornate border, flat vector shapes, elegant gold and deep navy palette, no text

Related Models

README

FLUX.2 Klein Base 4B Text-to-Image

FLUX.2 Klein Base 4B Text-to-Image is a lightweight yet capable text-to-image generation model. Describe your vision in text and get quality images with fast generation — the most affordable option in the FLUX.2 Klein family.

Why Choose This?

  • Fast and affordable 4B parameter model optimized for quick turnaround at the lowest cost in the Klein series.

  • Good prompt adherence Accurately interprets prompts to generate images that match your description.

  • Flexible sizing Custom width and height controls for any aspect ratio.

  • Prompt Enhancer Built-in tool to automatically improve your prompts for better results.

  • Best value Ideal for rapid prototyping, batch processing, and budget-conscious projects.

Parameters

ParameterRequiredDescription
promptYesText description of the image you want to generate
widthNoOutput width in pixels (default: 1024)
heightNoOutput height in pixels (default: 1024)
seedNoRandom seed for reproducibility (-1 for random)

How to Use

  1. Write your prompt — describe the image including subject, style, lighting, and mood.
  2. Set size — adjust width and height for your desired dimensions.
  3. Set seed — use -1 for random, or specify a number for reproducibility.
  4. Run — submit and download the generated image.

Pricing

ItemCost
Per image$0.01

Simple flat-rate pricing regardless of image size.

Best Use Cases

  • Rapid Prototyping — Quickly test ideas and concepts at minimal cost.
  • Batch Generation — Lowest cost enables large-scale image production.
  • Creative Exploration — Iterate on prompts without budget concerns.
  • Drafts and Mockups — Generate initial visuals before refining with higher-tier models.
  • Learning and Testing — Experiment with prompting techniques affordably.

Pro Tips

  • Be specific in your prompts — include subject, style, lighting, colors, and atmosphere.
  • Use the same seed to reproduce identical outputs or compare prompt variations.
  • Start with 1024x1024 for balanced quality, adjust dimensions for specific needs.
  • Need higher quality? Try FLUX.2 Klein Base 9B Text-to-Image.
  • Need custom styles? Try FLUX.2 Klein Base 4B Text-to-Image LoRA.

Notes

  • Most affordable option in the FLUX.2 Klein series.
  • For best results, write detailed, descriptive prompts.

Related Models

Note:This website uses AI models provided by third parties.

Flux 2 Klein Base 4b Text To Image API — Quick start

Grab a WaveSpeedAI API key, then call POST https://api.wavespeed.ai/api/v3/wavespeed-ai/flux-2-klein-base-4b/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 2 Klein Base 4b Text To Image 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",
    "size": "1024*1024",
    "seed": -1
}
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-2-klein-base-4b/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=$(printf '%s' "$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
done
Node.js example
const submitUrl = "https://api.wavespeed.ai/api/v3/wavespeed-ai/flux-2-klein-base-4b/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 ${apiKey}`,
    "Content-Type": "application/json",
  },
  body: JSON.stringify({
        "prompt": "A cinematic shot of a city at sunset, soft golden light",
        "size": "1024*1024",
        "seed": -1
}),
});
const task = body.data ?? body;
if (!task.id) throw new Error("Submission response did not contain a prediction id");
const resultUrl = task.urls?.get ||
  `https://api.wavespeed.ai/api/v3/predictions/${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));
}
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",
    "size": "1024*1024",
    "seed": -1
}

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-2-klein-base-4b/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 = 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 2 Klein Base 4b Text To Image API — Frequently asked questions

What is the Flux 2 Klein Base 4b Text To Image API?

Flux 2 Klein Base 4b Text To Image is a WaveSpeedAI model for image generation, exposed as a REST API on WaveSpeedAI. FLUX.2 [klein] Base 4B is a compact 4-billion-parameter text-to-image model that delivers fast generation with quality results. Ready-to-use REST inference API, best performance, no cold starts, affordable pricing. You can call it programmatically or try it from the playground above.

How do I call the Flux 2 Klein Base 4b Text To Image 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 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-2-klein-base-4b-text-to-image.

How much does Flux 2 Klein Base 4b Text To Image cost per run?

Flux 2 Klein Base 4b Text To Image starts at $0.010 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 2 Klein Base 4b Text To Image accept?

Key inputs: `prompt`, `size`, `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-2-klein-base-4b-text-to-image.

How do I get started with the Flux 2 Klein Base 4b Text To Image 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 2 Klein Base 4b Text To Image outputs commercially?

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.