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meshy/v7.1/multi-image-to-3d

Meshy 7.1 Multi-Image-to-3D reconstructs textured, PBR-ready 3D models from one to four views of the same object, with 2K geometry resolution for finer detail and configurable topology, rigging, and animation for game assets, product visualization, and production workflows. Ready-to-use REST inference API, best performance, no coldstarts, affordable pricing.

image-to-3d
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3D

$1.44per run

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README

Meshy 7.1 Multi-Image to 3D

Meshy 7.1 Multi-Image to 3D reconstructs a textured 3D mesh from one to four images of the same object taken from different angles. Meshy 7.1 focuses on geometric detail: set geometry_resolution to 2k for finer surfaces and sharper silhouettes. It returns a GLB model with FBX, OBJ, and USDZ exports when available.

Why Choose This?

  • Finer geometric detail geometry_resolution goes up to 2k, capturing small surface details and cleaner silhouettes — useful for close-up renders and 3D printing.

  • Texture control Generate textured models, enable PBR maps, or guide textures with a prompt or reference image.

  • Production geometry controls Adjust topology, target polygon count, symmetry, and remeshing.

  • Optional rigging and animation Rig humanoid characters and apply animation presets in the same request.

  • Multiple export formats GLB output with FBX, OBJ, and USDZ exports when available.

Parameters

ParameterRequiredDescription
imagesYesOne to four images of the same object from different angles.
topologyNoMesh topology: quad or triangle. Default: triangle.
target_polycountNoTarget polygon count. Range: 100–300000. Default: 30000.
symmetry_modeNooff, auto, or on. Default: auto.
should_remeshNoEnable remeshing for cleaner topology. Default: true.
should_textureNoGenerate textures. Default: true.
enable_pbrNoGenerate metallic, roughness, and normal maps. Default: false.
geometry_resolutionNostandard or 2k. 2k generates finer geometric detail. Default: standard.
pose_modeNoOptional humanoid pose: a-pose or t-pose. Leave unselected for no specific pose.
texture_promptNoOptional text guidance for texture generation. Maximum length: 600 characters.
texture_imageNoOptional image used to guide texture generation.
enable_riggingNoAutomatically rig a humanoid character. Default: false.
rigging_height_metersNoApproximate character height in meters when rigging is enabled. Default: 1.7.
enable_animationNoApply an animation preset. Requires enable_rigging. Default: false.
animation_action_idNoAnimation preset ID. Range: 0–696. Default: 92.

Pricing

ConfigurationCost
Untextured mesh (should_texture: false)$0.96
Textured mesh$1.44
2k geometry resolution+$0.24
Auto-rigging+$0.24
Animation preset+$0.144

Example Costs

ConfigurationCost
Untextured mesh (should_texture: false)$0.96
Textured mesh$1.44
Textured mesh + 2K geometry$1.68
Textured mesh + auto-rigging$1.68
Textured mesh + 2K geometry + auto-rigging + animation$2.064

Other parameters do not add separate charges.

Pro Tips

  • Use 2k geometry for hero assets, close-up renders, and 3D printing; use standard for quick iteration.
  • Higher geometry resolution applies to standard geometry.
  • Use texture_prompt to describe materials such as metal, leather, ceramic, fabric, or plastic.
  • Enable rigging only for humanoid characters; animation requires rigging.
  • Use consistent views of the same object with matching lighting and 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.

v7.1 Multi Image To 3d API — Quick start

Grab a WaveSpeedAI API key, then call POST https://api.wavespeed.ai/api/v3/meshy/v7.1/multi-image-to-3d 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 v7.1 Multi Image To 3d below.

HTTP example
set -euo pipefail

: "${WAVESPEED_API_KEY:?Set WAVESPEED_API_KEY}"

REQUEST_BODY=$(cat <<'JSON'
{
    "images": [
        "https://interactive-examples.mdn.mozilla.net/media/cc0-images/painted-hand-298-332.jpg"
    ],
    "topology": "triangle",
    "target_polycount": 30000,
    "symmetry_mode": "auto",
    "should_remesh": true,
    "should_texture": true,
    "enable_pbr": false,
    "geometry_resolution": "standard",
    "pose_mode": "a-pose",
    "enable_rigging": false,
    "rigging_height_meters": 1.7,
    "enable_animation": false,
    "animation_action_id": 92
}
JSON
)

# 1. Submit the prediction.
SUBMIT_RESPONSE=$(curl --silent --show-error --fail-with-body \
  -X POST "https://api.wavespeed.ai/api/v3/meshy/v7.1/multi-image-to-3d" \
  -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/meshy/v7.1/multi-image-to-3d";
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 ${apiKey}`,
    "Content-Type": "application/json",
  },
  body: JSON.stringify({
        "images": [
                "https://interactive-examples.mdn.mozilla.net/media/cc0-images/painted-hand-298-332.jpg"
        ],
        "topology": "triangle",
        "target_polycount": 30000,
        "symmetry_mode": "auto",
        "should_remesh": true,
        "should_texture": true,
        "enable_pbr": false,
        "geometry_resolution": "standard",
        "pose_mode": "a-pose",
        "enable_rigging": false,
        "rigging_height_meters": 1.7,
        "enable_animation": false,
        "animation_action_id": 92
}),
});
const task = body.data ?? body;
if (!task.id) throw new Error("Submission response did not contain a prediction id");
const resultUrl = `https://api.wavespeed.ai/api/v3/predictions/${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 = {
    "images": [
        "https://interactive-examples.mdn.mozilla.net/media/cc0-images/painted-hand-298-332.jpg"
    ],
    "topology": "triangle",
    "target_polycount": 30000,
    "symmetry_mode": "auto",
    "should_remesh": True,
    "should_texture": True,
    "enable_pbr": False,
    "geometry_resolution": "standard",
    "pose_mode": "a-pose",
    "enable_rigging": False,
    "rigging_height_meters": 1.7,
    "enable_animation": False,
    "animation_action_id": 92
}

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/meshy/v7.1/multi-image-to-3d", 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)

v7.1 Multi Image To 3d API — Frequently asked questions

What is the v7.1 Multi Image To 3d API?

v7.1 Multi Image To 3d is a Meshy model for 3D asset generation from images, exposed as a REST API on WaveSpeedAI. Meshy 7.1 Multi-Image-to-3D reconstructs textured, PBR-ready 3D models from one to four views of the same object, with 2K geometry resolution for finer detail and configurable topology, rigging, and animation for game assets, product visualization, and production workflows. 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 v7.1 Multi Image To 3d 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/meshy/meshy-v7.1-multi-image-to-3d.

How much does v7.1 Multi Image To 3d cost per run?

v7.1 Multi Image To 3d starts at $1.44 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 v7.1 Multi Image To 3d accept?

Key inputs: `images`, `animation_action_id`, `enable_animation`, `enable_pbr`, `enable_rigging`, `geometry_resolution`. 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/meshy/meshy-v7.1-multi-image-to-3d.

How do I get started with the v7.1 Multi Image To 3d API?

Sign up for a free WaveSpeedAI account to claim starter credits, copy your API key from /accesskey, then call the endpoint shown in the API tab of the playground. The playground also auto-generates a code sample in Python, JavaScript, or cURL for the parameters you've set.

Can I use v7.1 Multi Image To 3d outputs commercially?

Commercial usage rights depend on the model's license, set by its provider (Meshy). Check the provider's applicable terms and WaveSpeedAI's Terms of Service before commercial use.

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Meshy 7.1 Multi-Image-to-3D API on WaveSpeedAI