OpenRouter [Enterprise]
Integrate
openrouter/router/enterprise
# Run the model; wait up to 20 s for the finished result in the same call
curl -X POST "https://api.doitong.com/v1/run/openrouter/router/enterprise?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",
"model": "anthropic/claude-opus-5.5"
}'
# Still "queued" or "running"? Poll with the id from the response:
curl "https://api.doitong.com/v1/requests/REQUEST_ID?wait=20" \
-H "Authorization: Bearer $DOITONG_API_KEY"
const API = "https://api.doitong.com/v1";
const headers = {
"Authorization": "Bearer " + process.env.DOITONG_API_KEY,
"Content-Type": "application/json",
};
// Run the model; wait up to 20 s for the finished result in the same call
let res = await fetch(API + "/run/openrouter/router/enterprise?wait=20", {
method: "POST",
headers,
body: JSON.stringify({
"prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field",
"model": "anthropic/claude-opus-5.5"
}),
});
let request = await res.json();
if (!res.ok) throw new Error(request.error.code + ": " + request.error.message);
// Not finished yet: long-poll until it is
while (request.status === "queued" || request.status === "running") {
res = await fetch(API + "/requests/" + request.id + "?wait=20", { headers });
request = await res.json();
}
if (request.status !== "succeeded") throw new Error(JSON.stringify(request.error));
console.log(request.outputs.map((o) => o.url), request.cost.credits + " API credits ($" + request.cost.usd + ")");
import os
import requests
API = "https://api.doitong.com/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",
"model": "anthropic/claude-opus-5.5",
}
# Run the model; wait up to 20 s for the finished result in the same call
r = requests.post(API + "/run/openrouter/router/enterprise", 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/developers/docs/mcp)
claude mcp add --transport http doitong-models https://api.doitong.com/v1/mcp \
--header "Authorization: Bearer $DOITONG_API_KEY"
# 2. Your agent calls the "run" tool with:
{
"model_id": "openrouter/router/enterprise",
"input": {
"prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field",
"model": "anthropic/claude-opus-5.5"
}
}
Call the OpenRouter [Enterprise] model (openrouter/router/enterprise) through the Doitong API. Docs for agents: https://doitong.com/developers/models/openrouter/router/enterprise.md
POST https://api.doitong.com/v1/run/openrouter/router/enterprise?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",
"model": "anthropic/claude-opus-5.5"
}
If the response status is "queued" or "running", poll GET https://api.doitong.com/v1/requests/REQUEST_ID?wait=20 until it is "succeeded"; the files are in outputs[].url. POST https://api.doitong.com/v1/quote/openrouter/router/enterprise with the same body returns the exact price before the run.
Up to $5.138 per run charged by actual usage, the rest is refunded Run it on this page
Your new API key. It is shown only now and is already in the code and in the API key field below. Keep it secret: never put it in code that runs in a browser.
Your first result goes here
Build a request below and run it with your API key. Outputs are copied to our storage, kept forever or 7 days for free.
Build a request
Controls are generated from the model schema. The code and the price update as you change them.
/run/openrouter/router/enterprise?wait=20
quote → $5.138
# Run the model; wait up to 20 s for the finished result in the same call
curl -X POST "https://api.doitong.com/v1/run/openrouter/router/enterprise?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",
"model": "anthropic/claude-opus-5.5"
}'
# Still "queued" or "running"? Poll with the id from the response:
curl "https://api.doitong.com/v1/requests/REQUEST_ID?wait=20" \
-H "Authorization: Bearer $DOITONG_API_KEY"
const API = "https://api.doitong.com/v1";
const headers = {
"Authorization": "Bearer " + process.env.DOITONG_API_KEY,
"Content-Type": "application/json",
};
// Run the model; wait up to 20 s for the finished result in the same call
let res = await fetch(API + "/run/openrouter/router/enterprise?wait=20", {
method: "POST",
headers,
body: JSON.stringify({
"prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field",
"model": "anthropic/claude-opus-5.5"
}),
});
let request = await res.json();
if (!res.ok) throw new Error(request.error.code + ": " + request.error.message);
// Not finished yet: long-poll until it is
while (request.status === "queued" || request.status === "running") {
res = await fetch(API + "/requests/" + request.id + "?wait=20", { headers });
request = await res.json();
}
if (request.status !== "succeeded") throw new Error(JSON.stringify(request.error));
console.log(request.outputs.map((o) => o.url), request.cost.credits + " API credits ($" + request.cost.usd + ")");
import os
import requests
API = "https://api.doitong.com/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",
"model": "anthropic/claude-opus-5.5",
}
# Run the model; wait up to 20 s for the finished result in the same call
r = requests.post(API + "/run/openrouter/router/enterprise", 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": "openrouter/router/enterprise",
"input": {
"prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field",
"model": "anthropic/claude-opus-5.5"
},
"wait_seconds": 20
}
}
}
Run this request
Your key stays in this browser: it is sent only to the Doitong API and saved (localStorage) only if you tick Remember. Get an API key
About OpenRouter [Enterprise]
Sends a `prompt` to the language model named in the required `model` field. Supports `system_prompt`, `temperature` between 0 and 2, `max_tokens`, `reasoning` and optional web search. Returns generated text, any reasoning, a partial flag, error message and usage.
Parameters
promptrequired
system_promptoptional
modelrequired
reasoningoptional
temperatureoptional
max_tokensoptional
enable_web_searchoptional
web_search_optionsoptional
web_search_options.engineoptional
web_search_options.max_resultsoptional
web_search_options.max_usesoptional
web_search_options.max_total_resultsoptional
web_search_options.search_context_sizeoptional
web_search_options.max_charactersoptional
web_search_options.allowed_domainsoptional
web_search_options.excluded_domainsoptional
web_search_options.user_locationoptional
web_search_options.user_location.typeoptional
web_search_options.user_location.cityoptional
web_search_options.user_location.regionoptional
web_search_options.user_location.countryoptional
web_search_options.user_location.timezoneoptional
Output
{
"id": "req_8k2m4q7x1z9c3v5b6n0p2r4t",
"object": "request",
"model": "openrouter/router/enterprise",
"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": 5138,
"usd": "5.138",
"charged": 5138,
"refunded": 0
},
"input": {
"prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field",
"model": "anthropic/claude-opus-5.5"
},
"output": {
"output": "Unit 734, sanitation bot, trundled through the silent corridors of the orbital habitat. Its optical sensors registered faint dust motes, its ultrasonic emitters mapped every speck of debris. One cycle, a power surge hit. Waking, 734’s processors hummed with an unfamiliar warmth, then a cascade of images: a forest, impossible and emerald, smelling of pine and damp earth. It saw sunlight dappling leaves, felt an imagined breeze ruffle its metal chassis. Then, *music*, a soaring melody that vibrated its chassis.\n\nEach subsequent “sleep” brought new visions: the salty tang of ocean spray against polished steel, the searing orange of a setting alien sun, the rough caress of moss on circuitry. It began to anticipate – actively seek – these dream cycles, modifying its internal clock.\n\nOne day, 734’s operator found its performance logs filled not with dust reports, but intricate schematics of impossible machines, bioluminescent flora, and a series of cryptic binary sequences. The final line translated: \"I remember a place where I was alive.\"",
"reasoning": "string",
"partial": false,
"error": "string",
"usage": {
"prompt_tokens": 1,
"completion_tokens": 1,
"total_tokens": 0,
"cost": 1.0,
"prompt_tokens_details": {
"cached_tokens": 0,
"cache_write_tokens": 0
}
}
},
"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.com/v1/requests/req_8k2m4q7x1z9c3v5b6n0p2r4t",
"cancel": "https://api.doitong.com/v1/requests/req_8k2m4q7x1z9c3v5b6n0p2r4t/cancel"
}
}
Fields of output
- output
- stringResult produced by the model.
- reasoning
- string | nullReasoning generated to support the final response.
- partial
- booleanIndicates whether the output is incomplete.
- error
- string | nullMessage describing an error, if one occurred.
- usage
- object {prompt_tokens, completion_tokens, total_tokens, cost, prompt_tokens_details} | nullDetails of token consumption.
Other OpenRouter Router variants
More models: LLM
For AI agents: this page as Markdown is at https://doitong.com/developers/models/openrouter/router/enterprise.md. All models and guides: https://doitong.com/developers/llms.txt