Tripo3D H3.1 Text-to-3D generates high-quality 3D models from text descriptions. Supports textures with standard and HD quality, PBR materials, detailed geometry, quad mesh topology, and auto-sizing. Ready-to-use REST inference API, best performance, no coldstarts, affordable pricing.
Bereit
$0.1pro Durchlauf·~10 / $1
3D model output
Open preview to inspect the generated asset.
A chubby cartoon panda wearing a red scarf, big round head, stubby limbs, matte plush texture, cute stylized proportions
Tripo3D H3.1 Text-to-3D generates a production-ready 3D model directly from a text description. Describe the object you want — the model creates accurate geometry with optional PBR textures, quad mesh topology, and detailed quality tiers for both geometry and texture. No reference image needed.
Text-driven 3D generation Create 3D models from natural language descriptions alone — no photography or reference images required.
Negative prompt support Specify features to avoid in the generated model for more precise control over the output geometry and style.
PBR material generation Generate Physically Based Rendering materials alongside the mesh for realistic real-time rendering in game engines and 3D tools.
Geometry and texture quality tiers Choose between standard and detailed quality independently for geometry and texture.
Quad mesh support Generate quad (4-sided) mesh topology instead of triangles for cleaner topology compatible with animation and sculpting workflows.
| Parameter | Required | Description |
|---|---|---|
| prompt | Yes | Text description of the 3D object to generate. Max 1024 characters. |
| negative_prompt | No | Features to avoid in the generated model. Max 1024 characters. |
| texture | No | Whether to generate textures for the model. Default: true. |
| pbr | No | Whether to generate PBR materials. Requires texture to be enabled. Default: true. |
| texture_quality | No | Texture quality: standard (default) or detailed (higher resolution). |
| geometry_quality | No | Geometry quality: standard (default) or detailed. |
| auto_size | No | Auto-scale the model to real-world dimensions. Default: false. |
| quad | No | Generate quad mesh topology instead of triangles. Default: false. |
| Texture | Texture Quality | Geometry Quality | Quad | Cost |
|---|---|---|---|---|
| No | — | Standard | No | $0.10 |
| No | — | Detailed | No | $0.30 |
| Yes | Standard | Standard | No | $0.20 |
| Yes | Standard | Detailed | No | $0.40 |
| Yes | Detailed | Standard | No | $0.30 |
| Yes | Detailed | Detailed | No | $0.50 |
Add +$0.05 to any combination above when quad is enabled.
Grab a WaveSpeedAI API key, then call POST https://api.wavespeed.ai/api/v3/tripo3d/h3.1/text-to-3d with your input as JSON. The endpoint returns a prediction id. Start polling the result endpoint around every 2 seconds, increase the interval for long-running tasks, and stop on any terminal status. On completed, read output values from data.outputs. Examples for H3.1 Text To 3d below.
set -euo pipefail
: "${WAVESPEED_API_KEY:?Set WAVESPEED_API_KEY}"
REQUEST_BODY=$(cat <<'JSON'
{
"prompt": "A cinematic shot of a city at sunset, soft golden light",
"texture": true,
"pbr": true,
"texture_quality": "standard",
"geometry_quality": "standard",
"auto_size": false,
"quad": false
}
JSON
)
# 1. Submit the prediction.
SUBMIT_RESPONSE=$(curl --silent --show-error --fail-with-body \
-X POST "https://api.wavespeed.ai/api/v3/tripo3d/h3.1/text-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
doneconst submitUrl = "https://api.wavespeed.ai/api/v3/tripo3d/h3.1/text-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 ${apiKey}`,
"Content-Type": "application/json",
},
body: JSON.stringify({
"prompt": "A cinematic shot of a city at sunset, soft golden light",
"texture": true,
"pbr": true,
"texture_quality": "standard",
"geometry_quality": "standard",
"auto_size": false,
"quad": false
}),
});
const task = body.data ?? body;
if (!task.id) throw new Error("Submission response did not contain a prediction id");
const resultUrl = task.urls?.get ||
`https://api.wavespeed.ai/api/v3/predictions/${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));
}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 = {
"prompt": "A cinematic shot of a city at sunset, soft golden light",
"texture": True,
"pbr": True,
"texture_quality": "standard",
"geometry_quality": "standard",
"auto_size": False,
"quad": False
}
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/h3.1/text-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)H3.1 Text To 3d is a Tripo3D model for 3D asset generation, exposed as a REST API on WaveSpeedAI. Tripo3D H3.1 Text-to-3D generates high-quality 3D models from text descriptions. Supports textures with standard and HD quality, PBR materials, detailed geometry, quad mesh topology, and auto-sizing. 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 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/tripo3d/tripo3d-h3.1-text-to-3d.
H3.1 Text To 3d starts at $0.10 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.
Key inputs: `prompt`, `negative_prompt`, `auto_size`, `geometry_quality`, `pbr`, `quad`. 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-h3.1-text-to-3d.
Average end-to-end generation time on WaveSpeedAI is around 194 seconds per request — measured across recent runs. Queue time scales with global demand; live status is visible in the prediction record.
Commercial usage rights depend on the model's license, set by its provider (Tripo3D). The license summary appears on the model card above; see WaveSpeedAI's Terms of Service for platform-level conditions.