Nemotron 3 Nano Omni
I-integrate
nvidia/nemotron-3-nano-omni
# 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/nvidia/nemotron-3-nano-omni?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 $DOITONG_API_KEY"
const API = "https://api.doitong.ru/v1";
const headers = {
"Authorization": "Bearer " + process.env.DOITONG_API_KEY,
"Content-Type": "application/json",
};
// Run the model; wait up to 20 s for the finished result in the same call
let res = await fetch(API + "/run/nvidia/nemotron-3-nano-omni?wait=20", {
method: "POST",
headers,
body: JSON.stringify({
"prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field"
}),
});
let request = await res.json();
if (!res.ok) throw new Error(request.error.code + ": " + request.error.message);
// Not finished yet: long-poll until it is
while (request.status === "queued" || request.status === "running") {
res = await fetch(API + "/requests/" + request.id + "?wait=20", { headers });
request = await res.json();
}
if (request.status !== "succeeded") throw new Error(JSON.stringify(request.error));
console.log(request.outputs.map((o) => o.url), request.cost.credits + " API credits ($" + 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/nvidia/nemotron-3-nano-omni", 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/fil/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": "nvidia/nemotron-3-nano-omni",
"input": {
"prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field"
}
}
Tawagin ang modelong Nemotron 3 Nano Omni (nvidia/nemotron-3-nano-omni) sa pamamagitan ng Doitong API. Dokumentasyon para sa mga agent: https://doitong.com/fil/developers/models/nvidia/nemotron-3-nano-omni.md
POST https://api.doitong.ru/v1/run/nvidia/nemotron-3-nano-omni?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"
}
Kung ang response status ay "queued" o "running", i-poll ang GET https://api.doitong.ru/v1/requests/REQUEST_ID?wait=20 hanggang maging "succeeded"; nasa outputs[].url ang mga file. Ang POST https://api.doitong.ru/v1/quote/nvidia/nemotron-3-nano-omni na may parehong body ay nagbabalik ng eksaktong presyo bago patakbuhin.
Kahilingang ito: ≈$0.01 10 kredito ng API · ≈ ₽1.07 Patakbuhin ito sa page na ito
Ang bago mong API key. Ipinapakita lang ito ngayon at nasa code at sa field ng API key sa ibaba na. Panatilihin itong sikreto: huwag kailanman ilagay sa code na tumatakbo sa browser.
Dito mapupunta ang iyong unang resulta
Bumuo ng kahilingan sa ibaba at patakbuhin ito gamit ang iyong API key. Kinokopya ang mga output sa aming storage, na pinananatili nang walang hanggan o 7 araw nang libre.
Bumuo ng kahilingan
Ang mga control ay binubuo mula sa schema ng modelo. Nagbabago ang code at presyo habang ina-adjust mo ang mga ito.
/run/nvidia/nemotron-3-nano-omni?wait=20
presyo → $0.01
# 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/nvidia/nemotron-3-nano-omni?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 $DOITONG_API_KEY"
const API = "https://api.doitong.ru/v1";
const headers = {
"Authorization": "Bearer " + process.env.DOITONG_API_KEY,
"Content-Type": "application/json",
};
// Run the model; wait up to 20 s for the finished result in the same call
let res = await fetch(API + "/run/nvidia/nemotron-3-nano-omni?wait=20", {
method: "POST",
headers,
body: JSON.stringify({
"prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field"
}),
});
let request = await res.json();
if (!res.ok) throw new Error(request.error.code + ": " + request.error.message);
// Not finished yet: long-poll until it is
while (request.status === "queued" || request.status === "running") {
res = await fetch(API + "/requests/" + request.id + "?wait=20", { headers });
request = await res.json();
}
if (request.status !== "succeeded") throw new Error(JSON.stringify(request.error));
console.log(request.outputs.map((o) => o.url), request.cost.credits + " API credits ($" + 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/nvidia/nemotron-3-nano-omni", 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": "nvidia/nemotron-3-nano-omni",
"input": {
"prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field"
},
"wait_seconds": 20
}
}
}
Patakbuhin ang kahilingang ito
Nananatili ang iyong key sa browser na ito: ipinapadala lamang ito sa Doitong API at sine-save (localStorage) lamang kung pipiliin mo ang Tandaan. Kumuha ng API key
Tungkol sa Nemotron 3 Nano Omni
Isang modelo ng wika na sumasagot sa mga prompt na teksto, na may opsyonal na `system_prompt` para gabayan ang pag-uugali. Itakda ang `reasoning_mode` sa `think` para makakuha ng tala ng reasoning bago ang sagot, o sa `no_think` para sa direktang tugon. Umaabot sa 20,000 ang `max_tokens`, at maaaring isaayos ang `temperature` at `top_p`. Dapat nasa Ingles ang mga prompt.
Mga parameter
promptkinakailangan
system_promptopsyonal
reasoning_modeopsyonal
max_tokensopsyonal
temperatureopsyonal
top_popsyonal
enable_safety_checkeropsyonal
Output
{
"id": "req_8k2m4q7x1z9c3v5b6n0p2r4t",
"object": "request",
"model": "nvidia/nemotron-3-nano-omni",
"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": 10,
"usd": "0.01",
"charged": 10,
"refunded": 0
},
"input": {
"prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field"
},
"output": {
"output": "The image shows a golden retriever puppy sitting on a wooden floor.",
"finish_reason": "stop",
"usage": {
"input_tokens": 1,
"output_tokens": 1
}
},
"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"
}
}
Mga field ng output
- output
- stringTekstong ginawa bilang tugon.
- finish_reason
- stringDahilan ng pagtatapos ng pagbuo.
- usage
- object {input_tokens, output_tokens}Pagkonsumo ng token na kaugnay ng kahilingan.
Iba pang variant ng Nemotron 3 Nano Omni
Higit pang modelo: LLM
Para sa mga AI agent: nasa Markdown ang pahinang ito sa https://doitong.com/fil/developers/models/nvidia/nemotron-3-nano-omni.md. Lahat ng modelo at gabay: https://doitong.com/developers/llms.txt