Nano Banana 2.1 is LIVE — Google's Latest | Try Now →

wavespeed-ai/firered-image-v1.1/edit

FireRed Image Edit V1.1 enables precise image editing with natural-language instructions, supporting both English and Chinese prompts with multi-image references. Ready-to-use REST inference API, best performance, no cold starts, affordable pricing.

Image Editing
Input

Drag & drop or click to upload

preview

The size of the generated media in pixels (width*height).

Idle

The same young man reimagined as a 1950s greaser, 
slicked-back hair, vintage leather jacket, 
standing under a classic diner neon sign at dusk, 
old American cars in the background. 
Film grain, warm retro tones, editorial portrait.

$0.15per run·~66 / $10

Next:

ExamplesView all

The same young man reimagined as a 1950s greaser, 
slicked-back hair, vintage leather jacket, 
standing under a classic diner neon sign at dusk, 
old American cars in the background. 
Film grain, warm retro tones, editorial portrait.

The same young man reimagined as a 1950s greaser, slicked-back hair, vintage leather jacket, standing under a classic diner neon sign at dusk, old American cars in the background. Film grain, warm retro tones, editorial portrait.

A man with short messy brown hair and a beard, wearing a dark gray 
long-sleeve shirt, bright genuine smile, happy cheerful expression, 
eyes crinkled with joy, laughing, same person same lighting same 
gray background, studio portrait photography, 
photorealistic, high quality

A man with short messy brown hair and a beard, wearing a dark gray long-sleeve shirt, bright genuine smile, happy cheerful expression, eyes crinkled with joy, laughing, same person same lighting same gray background, studio portrait photography, photorealistic, high quality

Let the woman in Figure 1 wear the clothes in Figure 2.

Let the woman in Figure 1 wear the clothes in Figure 2.

Related Models

README

FireRed Image V1.1 Edit

FireRed Image V1.1 Edit is a powerful multi-image editing model that transforms reference images based on text prompts. Upload up to 3 reference images and describe the desired output — the model generates new images that combine elements, styles, or characters from your references with cinematic quality and retro aesthetics.

Why Choose This?

  • Multi-image reference Combine elements from up to 3 reference images into a single cohesive output.

  • Style-aware editing Excels at editorial looks, film grain, retro tones, and cinematic aesthetics.

  • Flexible sizing Choose preset aspect ratios or custom dimensions — leave empty to preserve original proportions.

  • Character consistency Maintain subject identity while transforming style, setting, or mood.

  • Prompt Enhancer Built-in tool to automatically improve your descriptions.

Parameters

ParameterRequiredDescription
promptYesText description of the desired output
imagesYesReference images (max: 3, click "+ Add Item" to add more)
sizeNoAspect ratio: 1:1, 16:9, 9:16, 4:3, 3:4, 3:2, 2:3
widthNoCustom width in pixels (range: 256–1536)
heightNoCustom height in pixels (range: 256–1536)

How to Use

  1. Upload reference images — add up to 3 images for style, character, or scene guidance.
  2. Write your prompt — describe the desired output with style and mood details.
  3. Set size (optional) — choose a preset ratio, custom dimensions, or leave empty to keep original proportions.
  4. Use Prompt Enhancer (optional) — click to refine your description.
  5. Run — submit and download your edited image.

Pricing

OutputCost
Per image$0.15

Best Use Cases

  • Editorial Portraits — Create stylized portraits with film grain and retro aesthetics.
  • Character Styling — Transform subjects into different settings, eras, or moods.
  • Vintage Looks — Generate images with warm retro tones and classic Americana vibes.
  • Fashion & Lifestyle — Produce editorial-quality imagery for campaigns.
  • Creative Compositing — Combine elements from multiple reference images seamlessly.

Pro Tips

  • Describe the style explicitly — include details like "film grain," "warm retro tones," or "editorial portrait."
  • Reference images guide the output — use clear, high-quality images for best results.
  • Leave size empty to automatically preserve the original image proportions.
  • Include setting and mood details (e.g., "classic diner neon sign at dusk") for atmospheric results.
  • Use 1–2 reference images for simpler edits; add a third for complex multi-element compositions.

Notes

  • Both prompt and images are required fields.
  • Maximum 3 reference images can be uploaded.
  • If size is not specified, the model preserves the original image ratio.
  • Resolution range: 256–1536 pixels for both width and height.

Related Models

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.

Firered Image v1.1 Edit API — Quick start

Grab a WaveSpeedAI API key, then call POST https://api.wavespeed.ai/api/v3/wavespeed-ai/firered-image-v1.1/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 Firered Image v1.1 Edit 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"
    ]
}
JSON
)

# 1. Submit the prediction.
SUBMIT_RESPONSE=$(curl --silent --show-error --fail-with-body \
  -X POST "https://api.wavespeed.ai/api/v3/wavespeed-ai/firered-image-v1.1/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
done
Node.js example
const submitUrl = "https://api.wavespeed.ai/api/v3/wavespeed-ai/firered-image-v1.1/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 ${apiKey}`,
    "Content-Type": "application/json",
  },
  body: JSON.stringify({
        "prompt": "A cinematic shot of a city at sunset, soft golden light",
        "images": [
                "https://interactive-examples.mdn.mozilla.net/media/cc0-images/painted-hand-298-332.jpg"
        ]
}),
});
const task = body.data ?? body;
if (!task.id) throw new Error("Submission response did not contain a prediction id");
const resultUrl = `https://api.wavespeed.ai/api/v3/predictions/${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"
    ]
}

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/firered-image-v1.1/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)

Firered Image v1.1 Edit API — Frequently asked questions

What is the Firered Image v1.1 Edit API?

Firered Image v1.1 Edit is a WaveSpeedAI model for image editing, exposed as a REST API on WaveSpeedAI. FireRed Image Edit V1.1 enables precise image editing with natural-language instructions, supporting both English and Chinese prompts with multi-image references. 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 Firered Image v1.1 Edit 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/firered-image-v1.1-edit.

How much does Firered Image v1.1 Edit cost per run?

Firered Image v1.1 Edit starts at $0.15 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 Firered Image v1.1 Edit accept?

Key inputs: `prompt`, `images`. 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/firered-image-v1.1-edit.

How long does Firered Image v1.1 Edit take to generate?

Reported generation time on WaveSpeedAI is around 37 seconds per request. This is an estimate, not a latency guarantee; queue time and input settings can change the total wait. live status is visible in the prediction record.

Can I use Firered Image v1.1 Edit 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.

llms.txt — wavespeed-ai/firered-image-v1.1/edit for AI agents and LLMs