Hyper3D - Rodin V2.5 - Text to 3D
Integra
hyper3d/rodin/v2.5/text-to-3d
# Run the model; wait up to 20 s for the finished result in the same call
curl -X POST "https://api.doitong.ru/v1/run/hyper3d/rodin/v2.5/text-to-3d?wait=20" \
-H "Authorization: Bearer $DOITONG_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field"
}'
# Still "queued" or "running"? Poll with the id from the response:
curl "https://api.doitong.ru/v1/requests/REQUEST_ID?wait=20" \
-H "Authorization: Bearer $DOITONG_API_KEY"
const API = "https://api.doitong.ru/v1";
const headers = {
"Authorization": "Bearer " + process.env.DOITONG_API_KEY,
"Content-Type": "application/json",
};
// Run the model; wait up to 20 s for the finished result in the same call
let res = await fetch(API + "/run/hyper3d/rodin/v2.5/text-to-3d?wait=20", {
method: "POST",
headers,
body: JSON.stringify({
"prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field"
}),
});
let request = await res.json();
if (!res.ok) throw new Error(request.error.code + ": " + request.error.message);
// Not finished yet: long-poll until it is
while (request.status === "queued" || request.status === "running") {
res = await fetch(API + "/requests/" + request.id + "?wait=20", { headers });
request = await res.json();
}
if (request.status !== "succeeded") throw new Error(JSON.stringify(request.error));
console.log(request.outputs.map((o) => o.url), request.cost.credits + " API credits ($" + request.cost.usd + ")");
import os
import requests
API = "https://api.doitong.ru/v1"
headers = {"Authorization": "Bearer " + os.environ["DOITONG_API_KEY"]}
payload = {
"prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field",
}
# Run the model; wait up to 20 s for the finished result in the same call
r = requests.post(API + "/run/hyper3d/rodin/v2.5/text-to-3d", params={"wait": 20}, json=payload, headers=headers)
request = r.json()
if not r.ok:
raise RuntimeError(request["error"]["code"] + ": " + request["error"]["message"])
# Not finished yet: long-poll until it is
while request["status"] in ("queued", "running"):
request = requests.get(API + "/requests/" + request["id"], params={"wait": 20}, headers=headers).json()
if request["status"] != "succeeded":
raise RuntimeError(request["error"])
print([o["url"] for o in request["outputs"]], request["cost"]["credits"], "API credits", "$" + request["cost"]["usd"])
# 1. Connect once (Claude Code; Cursor, VS Code, Claude Desktop: https://doitong.com/it/developers/docs/mcp)
claude mcp add --transport http doitong-models https://api.doitong.ru/v1/mcp \
--header "Authorization: Bearer $DOITONG_API_KEY"
# 2. Your agent calls the "run" tool with:
{
"model_id": "hyper3d/rodin/v2.5/text-to-3d",
"input": {
"prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field"
}
}
Chiama il modello Hyper3D - Rodin V2.5 - Text to 3D (hyper3d/rodin/v2.5/text-to-3d) tramite Doitong API. Documentazione per gli agenti: https://doitong.com/it/developers/models/hyper3d/rodin/v2.5/text-to-3d.md
POST https://api.doitong.ru/v1/run/hyper3d/rodin/v2.5/text-to-3d?wait=20
Authorization: Bearer $DOITONG_API_KEY
Content-Type: application/json
{
"prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field"
}
Se lo stato della risposta è "queued" o "running", interroga GET https://api.doitong.ru/v1/requests/REQUEST_ID?wait=20 finché non diventa "succeeded"; i file si trovano in outputs[].url. POST https://api.doitong.ru/v1/quote/hyper3d/rodin/v2.5/text-to-3d con lo stesso body restituisce il prezzo esatto prima dell'esecuzione.
Questa richiesta: 0,40 $ 400 crediti API · ≈ 43,03 ₽ Esegui in questa pagina
La tua nuova chiave API. Viene mostrata solo ora ed è già presente nel codice e nel campo della chiave API qui sotto. Mantienila segreta: non inserirla mai nel codice eseguito in un browser.
Il tuo primo risultato apparirà qui
Crea una richiesta qui sotto ed eseguila con la tua chiave API. Gli output vengono copiati nella nostra archiviazione, conservati per sempre oppure 7 giorni gratuitamente.
Crea una richiesta
I controlli vengono generati dallo schema del modello. Il codice e il prezzo si aggiornano mentre li modifichi.
/run/hyper3d/rodin/v2.5/text-to-3d?wait=20
preventivo → 0,40 $
# Run the model; wait up to 20 s for the finished result in the same call
curl -X POST "https://api.doitong.ru/v1/run/hyper3d/rodin/v2.5/text-to-3d?wait=20" \
-H "Authorization: Bearer $DOITONG_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field"
}'
# Still "queued" or "running"? Poll with the id from the response:
curl "https://api.doitong.ru/v1/requests/REQUEST_ID?wait=20" \
-H "Authorization: Bearer $DOITONG_API_KEY"
const API = "https://api.doitong.ru/v1";
const headers = {
"Authorization": "Bearer " + process.env.DOITONG_API_KEY,
"Content-Type": "application/json",
};
// Run the model; wait up to 20 s for the finished result in the same call
let res = await fetch(API + "/run/hyper3d/rodin/v2.5/text-to-3d?wait=20", {
method: "POST",
headers,
body: JSON.stringify({
"prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field"
}),
});
let request = await res.json();
if (!res.ok) throw new Error(request.error.code + ": " + request.error.message);
// Not finished yet: long-poll until it is
while (request.status === "queued" || request.status === "running") {
res = await fetch(API + "/requests/" + request.id + "?wait=20", { headers });
request = await res.json();
}
if (request.status !== "succeeded") throw new Error(JSON.stringify(request.error));
console.log(request.outputs.map((o) => o.url), request.cost.credits + " API credits ($" + request.cost.usd + ")");
import os
import requests
API = "https://api.doitong.ru/v1"
headers = {"Authorization": "Bearer " + os.environ["DOITONG_API_KEY"]}
payload = {
"prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field",
}
# Run the model; wait up to 20 s for the finished result in the same call
r = requests.post(API + "/run/hyper3d/rodin/v2.5/text-to-3d", params={"wait": 20}, json=payload, headers=headers)
request = r.json()
if not r.ok:
raise RuntimeError(request["error"]["code"] + ": " + request["error"]["message"])
# Not finished yet: long-poll until it is
while request["status"] in ("queued", "running"):
request = requests.get(API + "/requests/" + request["id"], params={"wait": 20}, headers=headers).json()
if request["status"] != "succeeded":
raise RuntimeError(request["error"])
print([o["url"] for o in request["outputs"]], request["cost"]["credits"], "API credits", "$" + request["cost"]["usd"])
{
"jsonrpc": "2.0",
"id": 1,
"method": "tools/call",
"params": {
"name": "run",
"arguments": {
"model_id": "hyper3d/rodin/v2.5/text-to-3d",
"input": {
"prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field"
},
"wait_seconds": 20
}
}
}
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Informazioni su Hyper3D - Rodin V2.5 - Text to 3D
Genera un modello 3D da un `prompt` obbligatorio fino a 1024 caratteri. Scegli un `tier` da Gen-2.5-Minimum a Gen-2.5-Extreme-High (predefinito High), una dimensione della mesh in quad o triangle e un `material` come PBR o Shaded. Esporta in glb, usdz, fbx, obj o stl e imposta `seed` tra 0 e 65535.
Parametri
promptobbligatorio
tierfacoltativo
seedfacoltativo
geometry_file_formatfacoltativo
materialfacoltativo
quality_mesh_optionfacoltativo
texture_modefacoltativo
enable_creative_modefacoltativo
hd_texturefacoltativo
texture_delightfacoltativo
is_microfacoltativo
TAPosefacoltativo
bbox_conditionfacoltativo
bbox_condition.widthfacoltativo
bbox_condition.heightfacoltativo
bbox_condition.lengthfacoltativo
addonsfacoltativo
addons.high_packfacoltativo
enable_safety_checkerfacoltativo
Output
{
"id": "req_8k2m4q7x1z9c3v5b6n0p2r4t",
"object": "request",
"model": "hyper3d/rodin/v2.5/text-to-3d",
"status": "succeeded",
"created_at": "2026-10-20T12:00:00Z",
"started_at": "2026-10-20T12:00:02Z",
"completed_at": "2026-10-20T12:00:09Z",
"queue_position": null,
"cost": {
"credits": 400,
"usd": "0.40",
"charged": 400,
"refunded": 0
},
"input": {
"prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field"
},
"output": {
"model_mesh": {
"url": "https://content.doitong.com/dev-api/2026/10/20/req_8k2m4q7x1z9c3v5b6n0p2r4t/0-output.jpeg",
"content_type": "image/jpeg",
"file_name": "0-output.jpeg",
"file_size": 1843200
},
"model_meshes": [
{
"url": "https://content.doitong.com/dev-api/2026/10/20/req_8k2m4q7x1z9c3v5b6n0p2r4t/0-output.jpeg",
"content_type": "image/jpeg",
"file_name": "0-output.jpeg",
"file_size": 1843200
}
],
"seed": 42,
"textures": [
{
"url": "https://content.doitong.com/dev-api/2026/10/20/req_8k2m4q7x1z9c3v5b6n0p2r4t/0-output.jpeg",
"content_type": "image/jpeg",
"file_name": "0-output.jpeg",
"file_size": 1843200,
"width": 1024,
"height": 768
}
]
},
"outputs": [
{
"type": "file",
"url": "https://content.doitong.com/dev-api/2026/10/20/req_8k2m4q7x1z9c3v5b6n0p2r4t/0-output.jpeg",
"content_type": "image/jpeg",
"file_size": 1843200,
"stored": true
}
],
"error": null,
"metrics": {
"inference_seconds": 6.8
},
"urls": {
"self": "https://api.doitong.ru/v1/requests/req_8k2m4q7x1z9c3v5b6n0p2r4t",
"cancel": "https://api.doitong.ru/v1/requests/req_8k2m4q7x1z9c3v5b6n0p2r4t/cancel"
}
}
Campi dell'output
- model_mesh
- object {url, content_type, file_name, file_size}File contenente l'oggetto 3D generato.
- model_meshes
- array of object {url, content_type, file_name, file_size}File aggiuntivi dell'oggetto 3D generati da Hyper3D e restituiti oltre a model_mesh.
- seed
- integerSeed applicato durante la generazione.
- textures
- array of object {url, content_type, file_name, file_size, width, height}Texture prodotte per l'oggetto 3D.
Altre varianti di Hyper3D - Rodin V2.5
Altri modelli: Da testo a 3D
Per gli agenti AI: questa pagina in Markdown è disponibile all'indirizzo https://doitong.com/it/developers/models/hyper3d/rodin/v2.5/text-to-3d.md. Tutti i modelli e le guide: https://doitong.com/developers/llms.txt