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Z Image Turbo Image to Image

wavespeed-ai /

Z-Image-Turbo Image-to-Image is a 6 billion parameter model that enhances the quality of reference images (similar to upscaling) in sub-second time. Ready-to-use REST inference API, best performance, no cold starts, affordable pricing.

image-to-image
入力

待機中

A realistic, high-resolution photograph of an American woman, captured in natural daylight with soft, diffused lighting that enhances her features gently. She is positioned in a candid, relaxed pose—standing outdoors near a park bench, wearing casual, contemporary clothing: a light blue denim jacket, a white t-shirt, and dark jeans. Her long, wavy brown hair falls loosely over her shoulders, and she has a subtle, thoughtful expression as she looks slightly off-camera. The background is softly blurred (shallow depth of field), with hints of greenery, a distant streetlamp, and a few passing pedestrians. Shot on a full-frame DSLR with a 50mm prime lens, emphasizing natural textures, skin tones, and environmental detail. Cinematic composition, eye-level shot, natural color grading, and a subtle film grain texture for authentic photographic realism.

$0.0051回あたり·~200 / $1

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サンプルすべて表示

A realistic, high-resolution photograph of an American woman, captured in natural daylight with soft, diffused lighting that enhances her features gently. She is positioned in a candid, relaxed pose—standing outdoors near a park bench, wearing casual, contemporary clothing: a light blue denim jacket, a white t-shirt, and dark jeans. Her long, wavy brown hair falls loosely over her shoulders, and she has a subtle, thoughtful expression as she looks slightly off-camera. The background is softly blurred (shallow depth of field), with hints of greenery, a distant streetlamp, and a few passing pedestrians. Shot on a full-frame DSLR with a 50mm prime lens, emphasizing natural textures, skin tones, and environmental detail. Cinematic composition, eye-level shot, natural color grading, and a subtle film grain texture for authentic photographic realism.

A realistic, high-resolution photograph of an American woman, captured in natural daylight with soft, diffused lighting that enhances her features gently. She is positioned in a candid, relaxed pose—standing outdoors near a park bench, wearing casual, contemporary clothing: a light blue denim jacket, a white t-shirt, and dark jeans. Her long, wavy brown hair falls loosely over her shoulders, and she has a subtle, thoughtful expression as she looks slightly off-camera. The background is softly blurred (shallow depth of field), with hints of greenery, a distant streetlamp, and a few passing pedestrians. Shot on a full-frame DSLR with a 50mm prime lens, emphasizing natural textures, skin tones, and environmental detail. Cinematic composition, eye-level shot, natural color grading, and a subtle film grain texture for authentic photographic realism.

An old lady sit on the floor

An old lady sit on the floor

Transform into a long-haired woman wearing glasses, dressed in the same clothes, posing in the same way.

Transform into a long-haired woman wearing glasses, dressed in the same clothes, posing in the same way.

関連モデル

README

Z-Image Turbo Image-to-Image

Z-Image Turbo Image-to-Image is a versatile image generation model that offers a spectrum of modifications — from subtle enhancement to dramatic reimagination. The key is the strength parameter: at low values, it preserves your original image while enhancing quality (similar to upscaling); at high values, it uses your image as loose inspiration for entirely new creations.

This is not a simple editing tool — it's a generation engine that lets you control exactly how much of the original image to preserve.

Why Choose This?

  • Flexible transformation spectrum From near-lossless enhancement to complete style overhaul — all controlled by a single strength slider.

  • Quality enhancement mode At low strength, improve image quality, add detail, and sharpen without changing content.

  • Creative reimagination mode At high strength, use your image as a reference while dramatically changing style, composition, or subject.

  • Custom output sizing Set exact width and height for your output, independent of input dimensions.

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

  • Fast and affordable Turbo-optimized for quick generation at just $0.005 per image.

Understanding Strength

The strength parameter is the core of this model. It controls how much the output differs from your input image:

StrengthEffectUse Case
0.0 - 0.3Minimal change — enhances quality, adds detail, sharpensUpscaling, quality improvement, subtle refinement
0.3 - 0.6Moderate change — preserves structure, adjusts styleStyle tweaks, color grading, texture enhancement
0.6 - 0.8Significant change — keeps composition, transforms contentStyle transfer, artistic reinterpretation
0.8 - 1.0Maximum change — uses image as loose reference onlyCreative reimagination, dramatic transformation

Parameters

ParameterRequiredDescription
promptYesText description guiding the transformation
imageYesSource image to transform (upload or URL)
widthNoOutput width in pixels (default: 1024)
heightNoOutput height in pixels (default: 1024)
strengthNoTransformation intensity 0-1 (default: 0.6)
seedNoRandom seed for reproducibility (-1 for random)

How to Use

  1. Upload your image — drag and drop or paste a public URL.
  2. Write your prompt — describe the desired output or transformation.
  3. Set strength — low for enhancement, high for reimagination.
  4. Adjust output size — set width and height as needed.
  5. Run — submit and download the transformed image.

Pricing

ItemCost
Per image$0.005

Simple flat-rate pricing regardless of image size or strength setting.

Best Use Cases

  • Image Enhancement (strength 0-0.3) — Improve quality, add sharpness, enhance details without changing content.
  • Style Transfer (strength 0.5-0.8) — Apply new artistic styles while preserving composition.
  • Creative Reimagination (strength 0.8-1.0) — Use images as inspiration for entirely new creations.
  • Batch Processing — Affordable pricing enables large-scale image transformation.
  • Iterative Design — Quickly explore variations with different strength levels.

Pro Tips

  • Start with strength 0.5 to understand how the model interprets your image, then adjust.
  • For quality enhancement without content change, use strength below 0.3 with a prompt describing the desired quality.
  • For dramatic transformations, use strength above 0.8 with a detailed prompt describing the new style.
  • The prompt matters more at higher strength values; at low strength, the image dominates.
  • Use the same seed to compare different strength levels on the same image.

Notes

  • Output dimensions can differ from input — set width and height to your target size.
  • At strength 0, output will be nearly identical to input (useful for testing).
  • At strength 1, output may differ significantly while retaining some compositional elements.

Related Models

注記:本サイトは第三者が提供するAIモデルを使用しています。

Z Image Turbo Image To Image API — Quick start

Grab a WaveSpeedAI API key, then call POST https://api.wavespeed.ai/api/v3/wavespeed-ai/z-image-turbo/image-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 Z Image Turbo Image 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",
    "image": "https://interactive-examples.mdn.mozilla.net/media/cc0-images/painted-hand-298-332.jpg",
    "size": "1024*1024",
    "strength": 0.6,
    "seed": -1,
    "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/z-image-turbo/image-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/z-image-turbo/image-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 ${apiKey}`,
    "Content-Type": "application/json",
  },
  body: JSON.stringify({
        "prompt": "A cinematic shot of a city at sunset, soft golden light",
        "image": "https://interactive-examples.mdn.mozilla.net/media/cc0-images/painted-hand-298-332.jpg",
        "size": "1024*1024",
        "strength": 0.6,
        "seed": -1,
        "output_format": "jpeg"
}),
});
const task = body.data ?? body;
if (!task.id) throw new Error("Submission response did not contain a prediction id");
const resultUrl = task.urls?.get ||
  `https://api.wavespeed.ai/api/v3/predictions/${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",
    "image": "https://interactive-examples.mdn.mozilla.net/media/cc0-images/painted-hand-298-332.jpg",
    "size": "1024*1024",
    "strength": 0.6,
    "seed": -1,
    "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/z-image-turbo/image-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)

Z Image Turbo Image To Image API — Frequently asked questions

What is the Z Image Turbo Image To Image API?

Z Image Turbo Image To Image is a WaveSpeedAI model for image editing, exposed as a REST API on WaveSpeedAI. Z-Image-Turbo Image-to-Image is a 6 billion parameter model that enhances the quality of reference images (similar to upscaling) in sub-second time. 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 Z Image Turbo Image 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/z-image-turbo-image-to-image.

How much does Z Image Turbo Image To Image cost per run?

Z Image Turbo Image To Image starts at $0.005 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 Z Image Turbo Image To Image accept?

Key inputs: `prompt`, `image`, `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/z-image-turbo-image-to-image.

How long does Z Image Turbo Image To Image take to generate?

Median end-to-end generation time on WaveSpeedAI is around 4 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 Z Image Turbo Image 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.

Z Image Turbo Image to Image | Fast Image Editing API | WaveSpeedAI