Seedance 2.5 Now Live | Try in Video Generator →
Home/Explore/Meshy/V7/Image To 3d

meshy/

Meshy V7 Image-to-3D turns a single reference image into a textured, PBR-ready 3D model with configurable topology, rigging, and animation for game assets, product visualization, 3D design, and production workflows. Ready-to-use REST inference API, best performance, no coldstarts, affordable pricing.

image-to-3d
Input

Idle

$1.32per run

ExamplesView all

Related Models

README

Meshy V7 Image to 3D

Meshy V7 Image to 3D converts a single reference image into a textured 3D mesh. It generates a GLB model and provides additional export formats such as FBX, OBJ, and USDZ when available.

Why Choose This?

  • Single-image 3D generation Create a 3D model from one clear reference image.

  • Standard and low-poly modes Use standard for detailed geometry or lowpoly for optimized low-polygon output.

  • Texture control Generate textured models, enable PBR materials, or guide texture style with a prompt or texture reference image.

  • Geometry controls Adjust topology, target polygon count, and remeshing behavior for different production needs.

  • Optional rigging and animation Enable humanoid rigging and animation presets when supported by the input object.

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

Parameters

ParameterRequiredDescription
imageYesReference image for 3D model creation.
model_typeNoModel type: standard for a detailed mesh or lowpoly for cleaner low-polygon geometry. Default: standard.
topologyNoMesh topology: quad or triangle. Default: triangle. This setting is ignored when model_type is lowpoly.
target_polycountNoTarget number of polygons for standard remeshed output. Range: 100–300000. Default: 30000.
symmetry_modeNoControls symmetry during model generation: off, auto, or on. Default: auto.
should_remeshNoEnable remeshing for cleaner topology. Default: true.
should_textureNoGenerate textures for the 3D model. Default: true.
enable_pbrNoGenerate PBR maps in addition to the base color texture. Default: false.
ultra_modeNoEnable higher-fidelity geometry with finer surface detail. Default: false.
pose_modeNoHumanoid pose used for generation: a-pose or t-pose. Default: a-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, including basic walking and running animations. Default: false.
rigging_height_metersNoApproximate character height in meters when rigging is enabled. Minimum: 0.01. Default: 1.7.
enable_animationNoApply an animation preset. Requires enable_rigging. Default: false.
animation_action_idNoMeshy animation preset ID, used only when animation is enabled. Range: 0–696. Default: 92.

How to Use

  1. Upload a reference image — Use a centered, well-lit image with one clear object or character.
  2. Choose model type — Select standard for detailed geometry or lowpoly for optimized output.
  3. Configure geometry optional — Adjust topology, target polygon count, or remeshing when needed.
  4. Enable textures optional — Use should_texture, enable_pbr, texture_prompt, or texture_image to control material output.
  5. Enable rigging optional — Use enable_rigging for humanoid characters that need a skeleton.
  6. Enable animation optional — Use enable_animation when an animation preset is needed. Rigging must also be enabled.
  7. Submit — Generate the 3D model and download the available exports.

Pricing

Pricing depends on texture generation, Ultra Mode, rigging, and animation settings.

ConfigurationCost
Standard mesh without textures$0.88
Textured mesh$1.32
Textured mesh with Ultra Mode$1.54
Auto-rigging+$0.22
Animation preset+$0.132

Example Costs

ConfigurationCost
Standard mesh without textures$0.88
Textured mesh$1.32
Textured mesh with Ultra Mode$1.54
Textured mesh + auto-rigging$1.54
Textured mesh + auto-rigging + animation$1.672
Ultra Mode textured mesh + auto-rigging + animation$1.892

Best Use Cases

  • Product 3D assets — Convert product images into 3D models for visualization or interactive previews.
  • Character models — Generate textured character meshes from reference images.
  • Game and real-time assets — Use low-poly mode for optimized 3D content.
  • E-commerce previews — Create 3D models for product display and marketing workflows.
  • Prototype modeling — Quickly turn visual concepts into editable 3D assets.
  • Rigged character workflows — Add rigging and animation for humanoid character use cases.

Pro Tips

  • Use a centered image with one clear object or character.
  • Avoid cluttered backgrounds, heavy shadows, reflections, or multiple overlapping objects.
  • Use standard mode when geometry quality matters.
  • Use lowpoly mode when performance or file size matters.
  • Enable textures when the final asset needs color, material, or surface detail.
  • Use texture_prompt to describe material details such as metal, leather, ceramic, fabric, or plastic.
  • Enable rigging only for suitable humanoid characters.
  • Use Meshy V7 Multi-Image to 3D when multi-view reconstruction is needed.
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 Image To 3d API — Quick start

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

HTTP example
set -euo pipefail

: "${WAVESPEED_API_KEY:?Set WAVESPEED_API_KEY}"

REQUEST_BODY=$(cat <<'JSON'
{
    "image": "https://interactive-examples.mdn.mozilla.net/media/cc0-images/painted-hand-298-332.jpg",
    "model_type": "standard",
    "topology": "triangle",
    "target_polycount": 30000,
    "symmetry_mode": "auto",
    "should_remesh": true,
    "should_texture": true,
    "enable_pbr": false,
    "ultra_mode": false,
    "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/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=$(printf '%s' "$TASK" | jq -r '.urls.get // empty')
if [ -z "$RESULT_URL" ]; then
  RESULT_URL="https://api.wavespeed.ai/api/v3/predictions/$PREDICTION_ID/result"
fi

# 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' "$RESULT" | jq '.outputs'; break ;;
    failed|cancelled|timeout) printf '%s\n' "$RESULT" | jq . >&2; exit 1 ;;
    created|processing) sleep 2 ;;
    *) printf 'Unexpected status: %s
' "$STATUS" >&2; exit 1 ;;
  esac
done
Node.js example
const submitUrl = "https://api.wavespeed.ai/api/v3/meshy/v7/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 ${apiKey}`,
    "Content-Type": "application/json",
  },
  body: JSON.stringify({
        "image": "https://interactive-examples.mdn.mozilla.net/media/cc0-images/painted-hand-298-332.jpg",
        "model_type": "standard",
        "topology": "triangle",
        "target_polycount": 30000,
        "symmetry_mode": "auto",
        "should_remesh": true,
        "should_texture": true,
        "enable_pbr": false,
        "ultra_mode": false,
        "pose_mode": "a-pose",
        "enable_rigging": false,
        "rigging_height_meters": 1.7,
        "enable_animation": false,
        "animation_action_id": 92
}),
});
const task = body.data ?? body;
if (!task.id) throw new Error("Submission response did not contain a prediction id");
const resultUrl = task.urls?.get ||
  `https://api.wavespeed.ai/api/v3/predictions/${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"].includes(result.status)) throw new Error(JSON.stringify(result));
  if (!["created", "processing"].includes(result.status)) throw new Error("Unexpected status: " + result.status);
  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 = {
    "image": "https://interactive-examples.mdn.mozilla.net/media/cc0-images/painted-hand-298-332.jpg",
    "model_type": "standard",
    "topology": "triangle",
    "target_polycount": 30000,
    "symmetry_mode": "auto",
    "should_remesh": True,
    "should_texture": True,
    "enable_pbr": False,
    "ultra_mode": False,
    "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/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 = task.get("urls", {}).get("get") or 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"}:
        raise RuntimeError(result)
    if status not in {"created", "processing"}:
        raise RuntimeError(f"Unexpected status: {status}")
    time.sleep(2)

v7 Image To 3d API — Frequently asked questions

What is the v7 Image To 3d API?

v7 Image To 3d is a Meshy model for 3D asset generation from images, exposed as a REST API on WaveSpeedAI. Meshy V7 Image-to-3D turns a single reference image into a textured, PBR-ready 3D model with configurable topology, rigging, and animation for game assets, product visualization, 3D design, 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 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 production-oriented Python, JavaScript, and cURL examples with timeouts, transient-error handling, and safe GET retries. Full request/response shape is documented at https://wavespeed.ai/docs/docs-api/meshy/meshy-v7-image-to-3d.

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

v7 Image To 3d starts at $1.32 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 Image To 3d accept?

Key inputs: `image`, `animation_action_id`, `enable_animation`, `enable_pbr`, `enable_rigging`, `model_type`. 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-image-to-3d.

How do I get started with the v7 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 Image To 3d outputs commercially?

Commercial usage rights depend on the model's license, set by its provider (Meshy). The license summary appears on the model card above; see WaveSpeedAI's Terms of Service for platform-level conditions.

Meshy V7 Image-to-3D API on WaveSpeedAI