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FLUX.2 [klein] Base 9B is a high-quality text-to-image model with 9B parameters, offering enhanced realism and crisper text generation. Ready-to-use REST inference API, best performance, no cold starts, affordable pricing.

text-to-image
इनपुट

निष्क्रिय

A cinematic cyberpunk noir still of a tired detective standing on a high balcony above a neon city at dawn, long dark coat, rain-soaked railing, holographic advertisements fading in the mist, sunrise breaking through smog, serious expression, realistic sci-fi film still, ultra-detailed

$0.015प्रति रन·~66 / $1

आगे:

उदाहरणसभी देखें

A cinematic cyberpunk noir still of a tired detective standing on a high balcony above a neon city at dawn, long dark coat, rain-soaked railing, holographic advertisements fading in the mist, sunrise breaking through smog, serious expression, realistic sci-fi film still, ultra-detailed

A cinematic cyberpunk noir still of a tired detective standing on a high balcony above a neon city at dawn, long dark coat, rain-soaked railing, holographic advertisements fading in the mist, sunrise breaking through smog, serious expression, realistic sci-fi film still, ultra-detailed

A cinematic portrait of an adult woman standing alone on a rainy city street at night, wet pavement reflecting neon lights, black coat, calm but emotional expression, soft bokeh background, realistic movie photography, shallow depth of field, moody lighting, ultra-detailed

A cinematic portrait of an adult woman standing alone on a rainy city street at night, wet pavement reflecting neon lights, black coat, calm but emotional expression, soft bokeh background, realistic movie photography, shallow depth of field, moody lighting, ultra-detailed

A warm lifestyle portrait of an adult woman sitting by a large cafe window in the morning, soft sunlight, coffee cup on the table, relaxed natural smile, cozy modern interior, shallow depth of field, premium editorial photography, photorealistic, highly detailed

A warm lifestyle portrait of an adult woman sitting by a large cafe window in the morning, soft sunlight, coffee cup on the table, relaxed natural smile, cozy modern interior, shallow depth of field, premium editorial photography, photorealistic, highly detailed

संबंधित मॉडल

README

WaveSpeed AI FLUX.2 Klein Base 9B Text-to-Image

WaveSpeed AI FLUX.2 Klein Base 9B Text-to-Image generates images from natural-language prompts with a simple interface for prompt input, output size selection, and optional seed control. It is suitable for concept art, creative ideation, marketing visuals, and other prompt-driven image generation workflows.

Why Choose This?

  • Prompt-based image generation Turn natural-language descriptions into generated images with minimal setup.

  • Simple control surface Only a few core inputs are required, making the workflow easy to use and integrate.

  • Flexible image size Use the size parameter to control the output dimensions.

  • Seed support for reproducibility Use seed to get more consistent generations across repeated runs.

  • Production-ready API Suitable for image generation tools, prototyping pipelines, and creative applications.

Parameters

ParameterRequiredDescription
promptYesText prompt describing the image you want to generate.
sizeNoOutput image size. Default: 1024*1024.
seedNoRandom seed for reproducibility. Use -1 for a random seed. Default: -1.

How to Use

  1. Write your prompt — describe the subject, style, lighting, composition, and mood you want.
  2. Choose size (optional) — set the output dimensions if you want something other than the default.
  3. Set a seed (optional) — use a fixed seed for more reproducible results, or -1 for random generation.
  4. Submit — run the model and download the generated image.

Example Prompt

A cinematic futuristic city street at night, neon reflections on wet pavement, atmospheric fog, ultra-detailed, dramatic lighting

Pricing

Just $0.015 per image.

Billing Rules

  • Each generated image costs $0.015
  • size and seed do not affect pricing
  • Pricing is fixed per generated image

Best Use Cases

  • Concept art — Explore visual ideas and creative directions quickly.
  • Marketing creatives — Generate visuals for campaigns, ads, and presentations.
  • Social media content — Produce prompt-driven images for posts and promotional content.
  • Creative prototyping — Test visual ideas before moving into heavier production workflows.
  • General image generation — Create still images from short or detailed prompts.

Pro Tips

  • Be specific in your prompt about subject, environment, style, and lighting.
  • Start with the default size for quick generation, then adjust if needed.
  • Use the same seed when you want more consistent variations of a concept.
  • Use -1 when you want a fresh random result each time.
  • Short, focused prompts often produce more controllable results than overly broad descriptions.

Notes

  • prompt is required.
  • size defaults to 1024*1024.
  • seed defaults to -1, which means random generation.
  • Pricing is fixed at $0.015 per image.

Related Models

नोट:यह वेबसाइट तृतीय पक्षों द्वारा प्रदान किए गए AI मॉडलों का उपयोग करती है। दस्तावेज़ की कीमतें केवल संदर्भ के लिए हैं और पुरानी हो सकती हैं। Generate बटन अनुमान दिखाता है; टास्क का अंतिम शुल्क ही मान्य होगा।

Flux 2 Klein Base 9b 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-9b/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 9b 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-9b/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-9b/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-9b/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 9b Text To Image API — Frequently asked questions

What is the Flux 2 Klein Base 9b Text To Image API?

Flux 2 Klein Base 9b Text To Image is a WaveSpeedAI model for image generation, exposed as a REST API on WaveSpeedAI. FLUX.2 [klein] Base 9B is a high-quality text-to-image model with 9B parameters, offering enhanced realism and crisper text generation. 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 9b 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-9b-text-to-image.

How much does Flux 2 Klein Base 9b Text To Image cost per run?

Flux 2 Klein Base 9b Text To Image starts at $0.015 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 9b 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-9b-text-to-image.

How long does Flux 2 Klein Base 9b Text To Image take to generate?

Median end-to-end generation time on WaveSpeedAI is around 11 seconds per request, based on recent successful runs. Queue time varies with global demand; live status is visible in the prediction record.

Can I use Flux 2 Klein Base 9b 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.