Tripo3D P2 Image-to-3D turns a single image into a 3D model with Tripo's P2 model with native quad topology (up to 50,000 triangles or 25,000 quads) for games and real-time pipelines. Ready-to-use REST inference API, best performance, no coldstarts, affordable pricing.
Idle
$1.32per run
Tripo3D P2 Image-to-3D generates a 3D model from a single image, with optional textures and PBR materials. Adjust the face count and choose triangle or quad output.
| Parameter | Required | Description |
|---|---|---|
| image | Yes | Image of the object (PNG, JPEG or WebP). |
| texture | No | Generate texture maps. Turn off (with pbr) for an untextured model at a lower price. Default: true. |
| pbr | No | Generate PBR materials (base color, metallic, roughness, normal). Turning it on also turns on texture. Default: true. |
| texture_quality | No | Texture quality: standard, detailed, extreme (8k), or fast (same texture size as standard). Options: standard, detailed, extreme, fast. Default: standard. |
| texture_version | No | Texture version. fast quality uses v3.5-20260815. Options: v3.0-20250812, v3.5-20260815. Default: v3.0-20250812. |
| delight | No | Remove the lighting baked into the source before texturing (texture model v3.5-20260815 only). Default: true. |
| quad | No | Output a native quad mesh (FBX). Default: false. |
| face_limit | No | Maximum number of faces: 48 to 50,000 triangles, or 48 to 25,000 quads. Omit for adaptive; 150+ for simple objects, 250+ for complex ones. |
| texture_alignment | No | What the texture follows: the source image colors or the generated geometry. Options: original_image, geometry. Default: original_image. |
| orientation | No | align_image rotates the model to the source image viewpoint (textured models only). Options: default, align_image. Default: default. |
| enable_image_autofix | No | Request input-image correction before generation. Default: false. |
| auto_size | No | Scale the model to real-world size in meters. Needs a textured model. Default: false. |
| export_uv | No | Unwrap UVs during generation. Default: true. |
| model_seed | No | Optional seed for geometry generation. |
| texture_seed | No | Optional seed for texture generation. |
| Configuration | Price per request |
|---|---|
| Geometry only | $1.20 |
| With standard or fast textures | $1.32 |
| With detailed textures | $1.44 |
| With extreme (8k) textures | $1.56 |
Quad output does not add a separate charge.
For geometry-only output, turn off both texture and pbr. Enabling pbr also enables textures.
texture and pbr for an untextured model.fast uses the same texture size and price as standard and selects texture version v3.5-20260815.delight affects texturing only with texture version v3.5-20260815; older texture versions ignore it.auto_size estimates real-world scale and requires textured output.Grab a WaveSpeedAI API key, then call POST https://api.wavespeed.ai/api/v3/tripo3d/p2/image-to-3d with your input as JSON. The endpoint returns a prediction id. Start polling the result endpoint around every 2 seconds, increase the interval for long-running tasks, and stop on any terminal status. On completed, read output values from data.outputs. Examples for P2 Image To 3d below.
set -euo pipefail
: "${WAVESPEED_API_KEY:?Set WAVESPEED_API_KEY}"
REQUEST_BODY=$(cat <<'JSON'
{
"image": "https://interactive-examples.mdn.mozilla.net/media/cc0-images/painted-hand-298-332.jpg",
"texture": true,
"pbr": true,
"texture_quality": "standard",
"texture_version": "v3.0-20250812",
"delight": true,
"quad": false,
"texture_alignment": "original_image",
"orientation": "default",
"enable_image_autofix": false,
"auto_size": false,
"export_uv": true
}
JSON
)
# 1. Submit the prediction.
SUBMIT_RESPONSE=$(curl --silent --show-error --fail-with-body \
-X POST "https://api.wavespeed.ai/api/v3/tripo3d/p2/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
doneconst submitUrl = "https://api.wavespeed.ai/api/v3/tripo3d/p2/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 ${apiKey}`,
"Content-Type": "application/json",
},
body: JSON.stringify({
"image": "https://interactive-examples.mdn.mozilla.net/media/cc0-images/painted-hand-298-332.jpg",
"texture": true,
"pbr": true,
"texture_quality": "standard",
"texture_version": "v3.0-20250812",
"delight": true,
"quad": false,
"texture_alignment": "original_image",
"orientation": "default",
"enable_image_autofix": false,
"auto_size": false,
"export_uv": true
}),
});
const task = body.data ?? body;
if (!task.id) throw new Error("Submission response did not contain a prediction id");
const resultUrl = `https://api.wavespeed.ai/api/v3/predictions/${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));
}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,
"quad": 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/p2/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)P2 Image To 3d is a Tripo3D model for 3D asset generation from images, exposed as a REST API on WaveSpeedAI. Tripo3D P2 Image-to-3D turns a single image into a 3D model with Tripo's P2 model with native quad topology (up to 50,000 triangles or 25,000 quads) for games and real-time pipelines. Ready-to-use REST inference API, best performance, no coldstarts, affordable pricing. You can call it programmatically or try it from the playground above.
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-p2-image-to-3d.
P2 Image To 3d starts at $1.32 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.
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-p2-image-to-3d.
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.
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.