Meshy Resize API Documentation

Meshy Resize API Documentation

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Meshy Resize scales a 3D model to a real-world height or size and sets its origin. Ready-to-use REST inference API, best performance, no coldstarts, affordable pricing.

Features

Meshy Resize adjusts the real-world scale and origin of an existing 3D model. Set a target height, resize by the longest side, or let the model estimate an appropriate real-world size automatically.


Why Choose This?

  • Real-world sizing — Resize a model using dimensions measured in meters.
  • Flexible sizing methods — Set the total height, longest side, or use automatic size estimation.
  • Proportional scaling — Resize the model while preserving its proportions.
  • Origin control — Place the model origin at the bottom or center.
  • Multiple 3D formats — Supports common formats including GLB, GLTF, FBX, OBJ, and STL.

Parameters

ParameterRequiredDescription
modelYesSource 3D model in GLB, GLTF, FBX, OBJ, or STL format.
resize_heightConditionalTarget model height in meters. Must be greater than 0.
resize_longest_sideConditionalTarget length of the model’s longest side in meters. Must be greater than 0.
auto_sizeConditionalAutomatically estimate the object’s real-world height and resize the model accordingly.
origin_atNoPosition of the model origin after resizing: bottom or center. Default: bottom.

Use exactly one of resize_height, resize_longest_side, or auto_size=true.


How to Use

  1. Upload a model — Provide the source 3D file.
  2. Choose a sizing method — Set resize_height, set resize_longest_side, or enable auto_size.
  3. Choose the origin — Select bottom or center.
  4. Submit — Resize and retrieve the processed model.

Pricing

$0.04 per model.

Sizing method and origin placement do not add separate charges.


Best Use Cases

  • 3D printing — Scale models to a specific real-world size before slicing.
  • Product visualization — Match digital assets to approximate physical dimensions.
  • Game and scene assets — Normalize model scale before importing into a scene.
  • Asset preparation — Standardize model dimensions across different sources.
  • Origin adjustment — Move the origin to the bottom or center for easier placement.

Pro Tips

  • Use resize_height when the model’s overall height is the important dimension.
  • Use resize_longest_side when the largest dimension should match a specific size.
  • Use auto_size when you want an estimated real-world scale without specifying a dimension manually.
  • Use origin_at=bottom when the model should sit naturally on a ground plane.
  • Use origin_at=center when centered positioning is more useful for downstream editing or placement.

Notes

  • Exactly one sizing method must be used: resize_height, resize_longest_side, or auto_size=true.
  • Explicit dimensions are measured in meters and must be greater than 0.
  • Model proportions are preserved during resizing.
  • auto_size estimates an appropriate real-world height and resizes the model to that scale.
  • origin_at supports bottom and center and defaults to bottom.
  • GLB, OBJ, FBX, and STL inputs keep their format in the resized result.
  • GLTF inputs are returned as GLB.

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'
{
  "model": "example",
  "auto_size": false,
  "origin_at": "bottom"
}
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/meshy/resize" \
  -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
modelstringYes--The 3D model to process (GLB, GLTF, FBX, OBJ or STL).
resize_heightnumberNo--Target height in meters.
resize_longest_sidenumberNo--Target longest side in meters (instead of resize_height).
auto_sizebooleanNofalse-Estimate the real-world size instead.
origin_atstringNobottombottom, centerWhere to place the model origin.

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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