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Tripo3D H3.0 Image-to-3D API

tripo3d/h3.0/image-to-3d

Tripo3D H3.0 Image-to-3D turns a single image into a 3D model with Tripo's previous-generation H3.0 model (up to 2 million faces), kept for consistency with earlier assets. Ready-to-use REST inference API, best performance, no coldstarts, affordable pricing.

Image to 3D
Input

Drag & drop or click to upload

preview

Idle

3D

$0.36per run·~27 / $10

ExamplesView all

3D

Related Models

README

Tripo3D H3.0 Image-to-3D

Tripo3D H3.0 Image-to-3D turns a single image into a 3D model with Tripo's previous-generation H3.0 model (up to 2 million faces), kept for consistency with earlier assets, powered by Tripo.

Why Choose This?

  • Official Tripo models The same Tripo models used in Tripo Studio, served as a REST API.

  • Production-ready output Download the result as a 3D file ready for game engines, DCC tools, AR and 3D printing.

  • Pay per task No subscription; you pay only for what you run.

Parameters

ParameterRequiredDescription
imageYesImage of the object (PNG, JPEG or WebP, up to 20 MB). A clean background and little occlusion work best.
textureNoGenerate texture maps. Turn off (with pbr) for an untextured model at a lower price. Default: true.
pbrNoGenerate PBR materials (base color, metallic, roughness, normal). Turning it on also turns on texture. Default: true.
texture_qualityNoTexture quality: standard, detailed (high resolution), extreme (8K) or fast (same size as standard, quicker; uses texture model v3.5-20260815). Options: standard, detailed, extreme, fast. Default: standard.
texture_versionNoTexture model. v3.5-20260815 is the newest; the fast quality and delight use it. Options: v3.0-20250812, v3.5-20260815. Default: v3.0-20250812.
delightNoRemove the lighting baked into the source before texturing (texture model v3.5-20260815 only). Default: true.
geometry_qualityNoGeometry quality: standard or detailed (Ultra, up to 2 million faces). Options: standard, detailed. Default: standard.
quadNoOutput a quad mesh (FBX). Without a face_limit it targets 10,000 faces. Default: false.
smart_low_polyNoGenerate a low-poly mesh with hand-crafted style topology. Best for simple objects. Default: false.
generate_partsNoGenerate the model as separate editable parts. Parts are untextured and triangle-only. Default: false.
face_limitNoMaximum number of faces. Omit for adaptive. Up to 1,000,000 (2,000,000 with detailed geometry, 150,000 with quad; 500 to 20,000 with smart_low_poly).
texture_alignmentNoWhat the texture follows: the source image colors or the generated geometry. Options: original_image, geometry. Default: original_image.
orientationNoalign_image rotates the model to the source image viewpoint (textured models only). Options: default, align_image. Default: default.
enable_image_autofixNoImprove a low-quality source image before generation. Takes longer. Default: false.
auto_sizeNoScale the model to real-world size in meters. Needs a textured model. Default: false.
export_uvNoUnwrap UVs during generation. Turn off for faster generation and a smaller file. Default: true.
model_seedNoSeed for the geometry: the same seed and input give the same mesh.
texture_seedNoSeed for the texture: keep model_seed and change texture_seed for new textures on the same mesh.

Pricing

Untextured $0.24; textured $0.36. Add-ons: detailed texture +$0.12, extreme (8K) texture +$0.24, detailed geometry +$0.24, quad +$0.06, smart_low_poly +$0.12, generate_parts +$0.24 (parts are untextured). fast costs the same as standard.

How to Use

  1. Upload an image — one object, clean background, little occlusion.
  2. Adjust the options you need, or keep the defaults.
  3. Submit — download the 3D file when it is ready.
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.

H3.0 Image To 3d API — Quick start

Grab a WaveSpeedAI API key, then call POST https://api.wavespeed.ai/api/v3/tripo3d/h3.0/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 H3.0 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",
    "texture": true,
    "pbr": true,
    "texture_quality": "standard",
    "texture_version": "v3.0-20250812",
    "delight": true,
    "geometry_quality": "standard",
    "quad": false,
    "smart_low_poly": false,
    "generate_parts": false,
    "texture_alignment": "original_image",
    "orientation": "default",
    "enable_image_autofix": false,
    "auto_size": false,
    "export_uv": true
}
JSON
)

# 1. Submit the prediction.
SUBMIT_RESPONSE=$(curl --silent --show-error --fail-with-body \
  -X POST "https://api.wavespeed.ai/api/v3/tripo3d/h3.0/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/tripo3d/h3.0/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 ${apiKey}`,
    "Content-Type": "application/json",
  },
  body: JSON.stringify({
        "image": "https://interactive-examples.mdn.mozilla.net/media/cc0-images/painted-hand-298-332.jpg",
        "texture": true,
        "pbr": true,
        "texture_quality": "standard",
        "texture_version": "v3.0-20250812",
        "delight": true,
        "geometry_quality": "standard",
        "quad": false,
        "smart_low_poly": false,
        "generate_parts": false,
        "texture_alignment": "original_image",
        "orientation": "default",
        "enable_image_autofix": false,
        "auto_size": false,
        "export_uv": true
}),
});
const task = body.data ?? body;
if (!task.id) throw new Error("Submission response did not contain a prediction id");
const resultUrl = `https://api.wavespeed.ai/api/v3/predictions/${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 = {
    "image": "https://interactive-examples.mdn.mozilla.net/media/cc0-images/painted-hand-298-332.jpg",
    "texture": True,
    "pbr": True,
    "texture_quality": "standard",
    "texture_version": "v3.0-20250812",
    "delight": True,
    "geometry_quality": "standard",
    "quad": False,
    "smart_low_poly": False,
    "generate_parts": False,
    "texture_alignment": "original_image",
    "orientation": "default",
    "enable_image_autofix": False,
    "auto_size": False,
    "export_uv": True
}

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/tripo3d/h3.0/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)

H3.0 Image To 3d API — Frequently asked questions

What is the H3.0 Image To 3d API?

H3.0 Image To 3d is a Tripo3D model for 3D asset generation from images, exposed as a REST API on WaveSpeedAI. Tripo3D H3.0 Image-to-3D turns a single image into a 3D model with Tripo's previous-generation H3.0 model (up to 2 million faces), kept for consistency with earlier assets. 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 H3.0 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/tripo3d/tripo3d-h3.0-image-to-3d.

How much does H3.0 Image To 3d cost per run or per second?

H3.0 Image To 3d starts at $0.36 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 H3.0 Image To 3d accept?

Key inputs: `image`, `auto_size`, `delight`, `enable_image_autofix`, `export_uv`, `face_limit`. 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/tripo3d/tripo3d-h3.0-image-to-3d.

How do I get started with the H3.0 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 H3.0 Image To 3d outputs commercially?

Commercial usage rights depend on the model's license, set by its provider (Tripo3D). Check the provider's applicable terms and WaveSpeedAI's Terms of Service before commercial use.

llms.txt — tripo3d/h3.0/image-to-3d for AI agents and LLMs