Minimax H3 Image Edit API Documentation

Minimax H3 Image Edit API Documentation

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

Features

MiniMax H3 Image Open-Weights Edit edits existing images using the open-weights release of MiniMax H3 Image. The first input image is treated as the editing target, while up to 8 additional images can be used as references.


Why Choose This?

  • Open-weights model — Use the open-weights release of MiniMax H3 Image.
  • Instruction-based editing — Describe the desired changes using natural-language instructions.
  • Multi-image references — Use up to 9 images in one request, addressed as <Picture 1>, <Picture 2>, and so on.
  • Up to 4K output — Choose 1k, 1.5k, 2k, 3k, or 4k.
  • Flexible framing — Generate square, portrait, landscape, tall, wide, and ultrawide outputs.
  • Multiple output formats — Export as JPEG, PNG, or WebP.
  • Seed control — Use a fixed seed when comparing edit variations.

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.
seedNoRandom seed. Use -1 for random generation.

How to Use

  1. Upload images — Place the image to edit first, followed by any reference images.
  2. Write an edit instruction — Describe what should change and how the references should be used.
  3. Reference images clearly — Use <Picture 1>, <Picture 2>, and so on when multiple images are involved.
  4. Choose output settings — Select the aspect ratio, resolution, and output format as needed.
  5. Set a seed optional — Use a fixed seed when comparing edit variations.
  6. Submit — Generate and retrieve the edited image.

Pricing

Pricing is based on the selected resolution.

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

ResolutionBase Price
1K$0.03
1.5K$0.045
2K$0.06
3K$0.12
4K$0.18

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.


Best Use Cases

  • Multi-image editing — Combine subjects, objects, or visual elements from several references.
  • Portrait editing — Adjust clothing, environment, styling, or composition.
  • Product editing — Use reference images to guide product appearance and placement.
  • Background changes — Place subjects into different environments.
  • Advertising concepts — Create image variations for campaign and promotional workflows.
  • High-resolution editing — Generate edited outputs at up to 4k.

Pro Tips

  • Describe the requested changes clearly.
  • Refer to each important input by its <Picture N> label.
  • Explain the role of each reference image when several are used.
  • Use fewer references when multiple images provide conflicting guidance.
  • Use a fixed seed when comparing prompt or reference changes.

Notes

  • The first image is the primary image being edited.
  • Up to 8 additional images can be used as references.
  • Leaving aspect_ratio unset uses the first image’s aspect ratio.

Authentication

For authentication details, please refer to the Authentication Guide.

API Endpoints

Submit Task & Query Result

set -euo pipefail

export WAVESPEED_API_KEY="your-api-key"

REQUEST_BODY=$(cat <<'JSON'
{
  "prompt": "A cinematic ocean wave at sunrise, highly detailed",
  "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 once. Never retry this request automatically:
# a retry after an unclear failure can create a second, billed task.
CHECK='The task may already exist. Check History or the predictions list before submitting again.'
if ! SUBMIT_RESPONSE=$(curl --silent --show-error --fail-with-body \
  --connect-timeout 10 --max-time 60 \
  -X POST "https://api.wavespeed.ai/api/v3/wavespeed-ai/minimax-h3-image/edit" \
  -H "Authorization: Bearer ${WAVESPEED_API_KEY}" \
  -H "Content-Type: application/json" \
  -d "${REQUEST_BODY}"); then
  printf 'Submit failed. %s\n' "${CHECK}" >&2
  exit 1
fi

TASK=$(printf '%s' "${SUBMIT_RESPONSE}" | jq 'if type == "object" and has("data") then .data else . end')
PREDICTION_ID=$(printf '%s' "${TASK}" | jq -r '.id // empty')
if [ -z "${PREDICTION_ID}" ]; then
  printf 'Submission response did not contain a prediction id. %s\n' "${CHECK}" >&2
  exit 1
fi
RESULT_URL="https://api.wavespeed.ai/api/v3/predictions/${PREDICTION_ID}/result"

# 2. Poll until the prediction reaches a final status.
BODY_FILE=$(mktemp)
trap 'rm -f "${BODY_FILE}"' EXIT
while true; do
  # Transient errors (429, 5xx) are retried, honoring Retry-After.
  HTTP_CODE=$(curl --silent --show-error --fail-with-body \
    --connect-timeout 10 --max-time 60 --retry 5 --retry-delay 2 \
    --output "${BODY_FILE}" --write-out '%{http_code}' \
    "${RESULT_URL}" \
    -H "Authorization: Bearer ${WAVESPEED_API_KEY}" || true)
  case "${HTTP_CODE}" in
    2??) ;;
    000|429|5??)  # dropped connection or temporary error: keep polling
      printf 'Task %s: HTTP %s, polling again in 10s\n' "${PREDICTION_ID}" "${HTTP_CODE}" >&2
      sleep 10; continue ;;
    *) printf 'Task %s: HTTP %s\n' "${PREDICTION_ID}" "${HTTP_CODE}" >&2
      cat "${BODY_FILE}" >&2; exit 1 ;;
  esac
  RESULT=$(jq 'if type == "object" and has("data") then .data else . end' "${BODY_FILE}")
  STATUS=$(printf '%s' "${RESULT}" | jq -r '.status // empty')

  case "${STATUS}" in
    completed) printf '%s\n' "${RESULT}" | jq '.outputs'; break ;;
    failed|cancelled|timeout|deleted)
      printf 'Task %s ended with status %s\n' "${PREDICTION_ID}" "${STATUS}" >&2
      printf '%s\n' "${RESULT}" | jq . >&2; exit 1 ;;
    *) sleep 2 ;;
  esac
done

Retry temporary errors only while polling, never the submit request. Errors, retries and timeouts

Parameters

Task Submission Parameters

Request Parameters

ParameterTypeRequiredDefaultRangeDescription
promptstringYes-The edit instruction. Refer to the input images as <Picture 1>, <Picture 2>, ... in order. Describe the result you want: the new scene, outfit, pose or style.
imagesarray<string>Yes-1 ~ 9 itemsInput images (1 to 9 URLs). The first image is the one being edited and sets the output aspect ratio unless aspect_ratio is given; the rest are references.
aspect_ratiostringNo-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, 21:9The aspect ratio of the generated image. If not specified, it follows the first input image.
resolutionstringNo1k1k, 1.5k, 2k, 3k, 4kTotal output resolution tier: 1k (~1 megapixels), 1.5k (~2.4 megapixels), 2k (~4 megapixels), 3k (~9.4 megapixels) or 4k (~16.8 megapixels).
output_formatstringNojpegjpeg, png, webpThe format of the output image.
seedintegerNo--The random seed to use for the generation. -1 means a random seed will be used.

Every model also accepts the global request options enable_sync_mode and enable_base64_output; see their pages for details.

Response Parameters

ParameterTypeDescription
codeintegerHTTP status code (e.g., 200 for success)
messagestringStatus message (e.g., “success”)
data.idstringUnique identifier for the prediction, Task Id
data.modelstringModel ID used for the prediction
data.outputsarrayOutput values, usually URL strings; some models return text strings or structured result objects (empty when status is not completed)
data.urlsobjectObject containing related API endpoints
data.statusstringTask status. completed is successful; failed, cancelled, timeout, and deleted are failure terminal statuses.
data.created_atstringISO timestamp of when the request was created (e.g., “2023-04-01T12:34:56.789Z”)
data.errorstringError message (empty if no error occurred)
data.timingsobjectObject containing timing details
data.timings.inferenceintegerInference time in milliseconds

Result Request Parameters

ParameterTypeRequiredDefaultDescription
idstringYes-Task ID

Result Response Parameters

ParameterTypeDescription
codeintegerHTTP status code (e.g., 200 for success)
messagestringStatus message (e.g., “success”)
dataobjectThe prediction data object containing all details
data.idstringUnique identifier for the prediction
data.modelstringModel ID used for the prediction
data.outputsarray<string | object>Array of generated outputs (empty when status is not completed). Items are usually URL strings, but may be text strings or structured result objects, depending on the model.
data.urlsobjectObject containing related API endpoints
data.statusstringStatus: completed is successful; failed, cancelled, timeout, and deleted are failure terminal statuses
data.created_atstringISO timestamp of when the request was created
data.errorstringError message (empty if no error occurred)
data.timingsobjectObject containing timing details
data.timings.inferenceintegerInference time in milliseconds
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