MiniMax H3 Image Open-Weights Edit LoRA API

wavespeed-ai/minimax-h3-image/edit-lora

MiniMax H3 Image, the open-weights release of MiniMax's image model, edits images from natural-language instructions with up to 9 input images and custom LoRA weights, native output from 1K to 4K. Ready-to-use REST inference API, best performance, no coldstarts, affordable pricing.

Image Editing
Input

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preview

Idle

Change the environment to a sunlit Mediterranean hotel terrace overlooking the sea, with pale stone walls, soft blue water, and warm natural daylight.
Change his outfit from the black leather jacket into an elegant cream linen blazer over a fitted black open-collar shirt, with subtle gold accessories.
Keep the result realistic, masculine, stylish, and editorial, with sharp facial detail, natural skin texture, refined fabric detail, and premium luxury fashion photography. Preserve the man’s exact face, hairstyle, body pose, hand position, and framing.

$0.03per run·~33 / $1

ExamplesView all

Change the environment to a sunlit Mediterranean hotel terrace overlooking the sea, with pale stone walls, soft blue water, and warm natural daylight.
Change his outfit from the black leather jacket into an elegant cream linen blazer over a fitted black open-collar shirt, with subtle gold accessories.
Keep the result realistic, masculine, stylish, and editorial, with sharp facial detail, natural skin texture, refined fabric detail, and premium luxury fashion photography. Preserve the man’s exact face, hairstyle, body pose, hand position, and framing.

Change the environment to a sunlit Mediterranean hotel terrace overlooking the sea, with pale stone walls, soft blue water, and warm natural daylight. Change his outfit from the black leather jacket into an elegant cream linen blazer over a fitted black open-collar shirt, with subtle gold accessories. Keep the result realistic, masculine, stylish, and editorial, with sharp facial detail, natural skin texture, refined fabric detail, and premium luxury fashion photography. Preserve the man’s exact face, hairstyle, body pose, hand position, and framing.

Change the season to winter: she wears a cream knitted sweater and a scarf, snow falling softly in a pine forest behind her.

Change the season to winter: she wears a cream knitted sweater and a scarf, snow falling softly in a pine forest behind her.

Dress him in a tailored navy suit and place him in a bright modern office with large windows. Keep his face unchanged.

Dress him in a tailored navy suit and place him in a bright modern office with large windows. Keep his face unchanged.

Related Models

README

MiniMax H3 Image Open-Weights Edit LoRA

MiniMax H3 Image Open-Weights Edit LoRA runs the open-weights release of MiniMax H3 Image (weights published by MiniMax). It edits an existing image from a text instruction: the first input image is the one being edited, and up to 8 more can be used as references, with up to 3 custom LoRA weights per request. Output is generated natively from 1k up to 4k.

Why Choose This?

  • Open-weights model — The open weights MiniMax released for H3 Image, the same model family as MiniMax H3 video.
  • LoRA support — Load up to 3 LoRA weights in one request, each with its own scale.
  • Instruction-based editing — Describe what should change; the first image is the editing target.
  • Multi-image references — Use up to 9 images, addressed as <Picture 1>, <Picture 2>, and so on.
  • Native output up to 4K — Choose 1k, 1.5k, 2k, 3k, or 4k; every tier is generated at its own size.
  • Built-in prompt enhancement — Short prompts in any language are expanded into a detailed description before generation.
  • Flexible framing — Square, portrait, landscape, and ultrawide aspect ratios.
  • Multiple output formats — Export as JPEG, PNG, or WebP.

Parameters

ParameterRequiredDescription
promptYesEdit instruction describing the desired result. Refer to input images as <Picture 1>, <Picture 2>, and so on.
imagesYesBetween 1 and 9 image URLs. The first image is edited; additional images are used as references.
aspect_ratioNoOutput aspect ratio: 1:1, 1:2, 2:1, 1:3, 3:1, 2:3, 3:2, 3:4, 4:3, 4:5, 5:4, 9:16, 16:9, 9:21, or 21:9. Defaults to the first image's aspect ratio.
resolutionNoOutput resolution: 1k, 1.5k, 2k, 3k, or 4k. Default: 1k.
output_formatNoOutput format: jpeg, png, or webp. Default: jpeg.
lorasNoUp to 3 LoRA weights. Each item uses {path, scale}, where path points to the LoRA file and scale controls its influence.
seedNoRandom seed. Use -1 for random generation.

Pricing

Pricing is based on the selected resolution, with a fixed $0.015 LoRA surcharge per generation included in the table.

The first input image is included in the base price. Each additional input image costs $0.01.

ResolutionBase Price
1K$0.045
1.5K$0.06
2K$0.075
3K$0.135
4K$0.195

Additional Images

Additional Reference ImagesAdditional Cost
1+$0.01
4+$0.04
8+$0.08

Aspect ratio, output format, and seed do not add separate charges.

Notes

  • prompt and images are required.
  • images supports between 1 and 9 inputs; the first is the image being edited.
  • resolution defaults to 1k; output_format defaults to jpeg.
  • Use seed=-1 for random seed selection.
  • Up to 3 LoRA weights per request, each as {path, scale}.

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.

Minimax H3 Image Edit Lora API — Quick start

Grab a WaveSpeedAI API key, then call POST https://api.wavespeed.ai/api/v3/wavespeed-ai/minimax-h3-image/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 Minimax H3 Image 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/minimax-h3-image/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/minimax-h3-image/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/minimax-h3-image/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)

Minimax H3 Image Edit Lora API — Frequently asked questions

What is the Minimax H3 Image Edit Lora API?

Minimax H3 Image Edit Lora is a WaveSpeedAI model for image editing, exposed as a REST API on WaveSpeedAI. MiniMax H3 Image, the open-weights release of MiniMax's image model, edits images from natural-language instructions with up to 9 input images and custom LoRA weights, native output from 1K to 4K. 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 Minimax H3 Image 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/minimax-h3-image-edit-lora.

How much does Minimax H3 Image Edit Lora cost per run or per second?

Minimax H3 Image Edit Lora starts at $0.03 per run or per second. 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 Minimax H3 Image Edit Lora accept?

Key inputs: `prompt`, `images`, `aspect_ratio`, `resolution`, `seed`, `loras`. 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/minimax-h3-image-edit-lora.

How long does Minimax H3 Image Edit Lora take to generate?

Reported generation time on WaveSpeedAI is around 53 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 Minimax H3 Image 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.

llms.txt — wavespeed-ai/minimax-h3-image/edit-lora for AI agents and LLMs