Global routing
Requests are routed across leading providers with health-aware node selection, tuned for responsive calls under production load.
Kimi, GLM, Qwen, Wan, DeepSeek and BytePlus, alongside GPT, Claude and Gemini — through a single OpenAI-compatible endpoint. Broader model choice, reliable routing, and usage-based billing with no minimum commitment.
OpenAI-compatible · change one line · pay only for what you use
import os
from openai import OpenAI
client = OpenAI(
api_key=os.environ["ONEAI_API_KEY"],
base_url="https://api.1ai.cloud/v1", # the only line you change
)
response = client.chat.completions.create(
model="kimi-k3",
messages=[{"role": "user", "content": "Say hello in one sentence."}],
)
print(response.choices[0].message.content)
import OpenAI from "openai";
const client = new OpenAI({
apiKey: process.env.ONEAI_API_KEY,
baseURL: "https://api.1ai.cloud/v1", // the only line you change
});
const response = await client.chat.completions.create({
model: "claude-sonnet-5",
messages: [{ role: "user", content: "Say hello in one sentence." }],
});
console.log(response.choices[0].message.content);
curl https://api.1ai.cloud/v1/chat/completions \
-H "Authorization: Bearer $ONEAI_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"model": "glm-5.2",
"messages": [{"role": "user", "content": "Say hello in one sentence."}],
"stream": false
}'
Most gateways give you one region's models. 1AI Cloud gives you the Chinese frontier labs and the Western ones behind the same key, the same schema and the same invoice.
Requests are routed across leading providers with health-aware node selection, tuned for responsive calls under production load.
Pay for the tokens and seconds you actually consume. No seats, no minimum commitment, no contract before you can run your first benchmark.
Kimi, GLM, HappyHorse, Qwen, Wan, DeepSeek and BytePlus sit next to GPT, Claude and Gemini in one catalogue with one request schema.
Multi-node scheduling is tuned continuously so API access stays responsive across the regions your users are actually in.
Standard /v1/chat/completions semantics. Existing SDKs, agents and frameworks keep working — you change base_url.
Technical and commercial support from named contacts on WeChat and Telegram — not a ticket queue — for teams scaling past prototype.
Any proxy works when every upstream is healthy. What matters is what happens when one provider rate-limits you mid-launch.
Send an ordered list of models. If the first upstream returns a rate limit, a timeout or a 5xx, the request moves down the list inside the same call — your application sees one response, not a retry loop you had to write yourself.
{
"model": "claude-sonnet-5",
"fallbacks": ["gpt-5.4", "glm-5.2", "kimi-k3"],
"messages": [ ... ]
}
SSE streaming, function calling and JSON-schema structured output are normalised across providers, so an agent written against one model runs against the others without a rewrite.
Every call — Chinese or Western model, text or video — lands in the same usage record, so cost attribution per key, per model and per project is one query rather than six invoices.
Because the schema is shared, moving a workload from a frontier model to a cheaper one is a config change. Benchmark on the expensive model, serve on the one that pays for itself.
Issue separate keys for staging, production and each teammate, and revoke any one of them without rotating the rest or touching the others' traffic.
Filter by provider or modality. Prices shown are per 1M tokens unless the row states otherwise — media models bill per generated second or per image.
Up to 1M context with native vision and configurable reasoning — built for coding, knowledge work and long-running agent tasks.
1M context and up to 128K output, plus function calling and structured output for long-running development workflows.
1M context with reasoning, function calling and built-in tools. This model remains in preview — treat availability as subject to change.
1M context, up to 384K output, tool calls and thinking modes for agentic and heavy reasoning workloads.
Text-to-video generation billed per generated second, at 720P and 1080P, for creative media pipelines alongside your text models.
Image generation with the first image free, then per-image billing that steps up only above 2.36M pixels.
If you already call an OpenAI-compatible endpoint, step four is a one-line diff.
Register and verify your account in the console.
Alipay or WeChat Pay. Balance is usage-based — no plan to pick.
Issue a scoped API key in one click. Revoke it just as fast.
Point base_url at 1AI Cloud and pick a model.
# 1 — install any OpenAI-compatible SDK
pip install openai
# 2 — set your key
export ONEAI_API_KEY="your-api-key"
# 3 — verify the key and list what you can route to
curl https://api.1ai.cloud/v1/models \
-H "Authorization: Bearer $ONEAI_API_KEY"
# 4 — send a request. swap `model` for any id in the catalogue.
curl https://api.1ai.cloud/v1/chat/completions \
-H "Authorization: Bearer $ONEAI_API_KEY" \
-H "Content-Type: application/json" \
-d '{"model":"kimi-k3","messages":[{"role":"user","content":"ping"}]}'
Text models are priced per 1M tokens in the currency shown. Media models bill per generated second or per image. Every row states its own billing unit.
A gateway sits between your application and every model you depend on. That position has to be earned, so here is exactly what it involves.
All API traffic runs over TLS. Keys are presented as bearer tokens and are never embedded in URLs or query strings.
Prompts and completions are passed through to the upstream provider to serve your request. They are not used to train models.
Every price on this page links to the provider's own pricing page, with the date we last checked it. Nothing is quoted without a source.
The API is OpenAI-compatible by design. If you ever want to leave, you change base_url back — there is nothing proprietary to unwind.
Issue one key per environment or per teammate. Revoking a compromised key does not interrupt any other traffic.
Three named sales and technical contacts, reachable on WeChat and Telegram, listed publicly on this page. No anonymous support queue.
Long-context models with tool calling, and a cheaper fallback for the routine steps in a multi-step run.
1M-context models let you skip aggressive chunking, and swap to a cheaper model for re-ranking passes.
Image and video generation billed per image or per generated second, on the same key as your text models.
Benchmark ten models against one prompt set without opening ten accounts or reconciling ten invoices.
Service policy on usage rights, refunds, and data handling.
1) Account responsibility. You are responsible for all activity under your account and any API key you issue. Keep keys private, scope each key to one project when possible, and revoke immediately if leakage is suspected.
2) Allowed usage. You may use the API for lawful and lawful-compliant product development, including internal testing and commercial services, but not for malware distribution, prompt injection infrastructure, data scraping at prohibited scale, or other activities that violate applicable laws.
3) Billing integrity. All requests are settled according to published pricing and the conversion rules shown in the pricing table. If a provider adjusts model availability or pricing, settlement follows the latest effective plan from the provider and your current console settings.
1) Balance usage. Top-ups are pre-funded balances. Consumption-based spending follows actual request usage and cannot be partially reversed once consumed.
2) Erroneous payments. If you report an accidental duplicate or clearly unauthorized charge within 14 calendar days and no usage is disputed, we will review and may issue a full or partial refund where applicable.
3) Service disruption. If a confirmed billing error is caused by service availability failure on our side, we will prioritize restoring balance credit or equivalent usage quota before final invoice settlement.
1) Data in requests. Prompts and responses are encrypted in transit and retained only as needed for reliability, anti-abuse controls, and operations. They are not used to train internal foundation models.
2) Retention. We keep request metadata for a limited period for audit and abuse defense, then delete it according to the retention window shown in the current console controls.
3) Third-party providers. For model output and any model-specific logs, upstream providers apply their own processing rules. If you have stricter enterprise requirements, request compliance settings before onboarding high-sensitivity workloads.
For legal and billing questions, mail [email protected]. You can also contact sales support through the existing Telegram / WeChat options below.
Working-hours contact target: response within one business day for account, billing, and support policy questions whenever possible.
Create a key, top up whatever you feel like risking, and send your first request in the next five minutes.
Message any of the contacts below.
Scan any QR code to add a sales contact.