This guide takes you from zero to your first model response with OpenPAI in under 5 minutes.
Step 1: Create an account
Open https://openp.ai in your browser and click Sign up in the top-right corner.
You can register or sign in with any of the following:
Email + password
GitHub (OAuth)
Telegram
LinuxDO
After signing up, new users automatically receive an initial trial credit you can use right away for test calls.
Step 2: Create an API key
Once signed in, open the Tokens page from the left-hand menu and click Add new token .
Fill in the following fields:
Field Meaning Recommendation Name For your own reference only e.g. my-app-prod Quota Max amount this token may spend (use -1 for unlimited) Cap each token’s quota in production Expiry Leave empty for no expiry Set a short window for temporary tests Model scope Models this token may call (empty = all) Tighten permissions as needed
After saving, the system generates an API key like sk-XXXXXXXXXXXXXXXX. Copy and store it immediately — you won’t be able to view it in full again after refreshing the page.
Step 3: Choose a model
OpenPAI integrates models from OpenAI, Anthropic, Google, DeepSeek, Qwen, Midjourney, Suno and more.
See the full list in the Models overview , or check available models and billing multipliers on the Models page of the console.
Common model IDs:
Use case Model ID Chat (cost-effective) gpt-5.4-mini claude-haiku-4-5 gemini-3.1-flash-liteChat (high quality) gpt-5.5 claude-opus-4-8 gemini-3.1-pro-preview gemini-3.5-flashReasoning gpt-5.5 o4-mini claude-opus-4-8 gemini-3.1-pro-previewText embeddings text-embedding-3-small text-embedding-3-large gemini-embedding-2Image generation gpt-image-2 dall-e-3 mj_imagine nano-banana-pro
Step 4: Send your first request
OpenPAI is OpenAI-compatible by default — just change your official SDK’s base_url to https://openp.ai/v1 and use the sk- key issued by OpenPAI.
cURL
Python (openai SDK)
Node.js
Go
curl https://openp.ai/v1/chat/completions \
-H "Authorization: Bearer $OPENPAI_API_KEY " \
-H "Content-Type: application/json" \
-d '{
"model": "gpt-5.5",
"messages": [
{"role": "system", "content": "You are a helpful assistant."},
{"role": "user", "content": "Introduce OpenPAI in one sentence"}
]
}'
from openai import OpenAI
client = OpenAI(
api_key = "sk-XXXXXXXXXXXXXXXX" ,
base_url = "https://openp.ai/v1" ,
)
resp = client.chat.completions.create(
model = "gpt-5.5" ,
messages = [
{ "role" : "system" , "content" : "You are a helpful assistant." },
{ "role" : "user" , "content" : "Introduce OpenPAI in one sentence" },
],
)
print (resp.choices[ 0 ].message.content)
import OpenAI from "openai" ;
const client = new OpenAI ({
apiKey: process . env . OPENPAI_API_KEY ,
baseURL: "https://openp.ai/v1" ,
});
const resp = await client . chat . completions . create ({
model: "gpt-5.5" ,
messages: [
{ role: "system" , content: "You are a helpful assistant." },
{ role: "user" , content: "Introduce OpenPAI in one sentence" },
],
});
console . log ( resp . choices [ 0 ]. message . content );
package main
import (
" context "
" fmt "
" github.com/sashabaranov/go-openai "
)
func main () {
cfg := openai . DefaultConfig ( "sk-XXXXXXXXXXXXXXXX" )
cfg . BaseURL = "https://openp.ai/v1"
client := openai . NewClientWithConfig ( cfg )
resp , err := client . CreateChatCompletion ( context . Background (),
openai . ChatCompletionRequest {
Model : "gpt-5.5" ,
Messages : [] openai . ChatCompletionMessage {
{ Role : openai . ChatMessageRoleUser , Content : "Introduce OpenPAI in one sentence" },
},
})
if err != nil {
panic ( err )
}
fmt . Println ( resp . Choices [ 0 ]. Message . Content )
}
A successful request returns JSON like the following:
{
"id" : "chatcmpl-..." ,
"object" : "chat.completion" ,
"created" : 1715750400 ,
"model" : "gpt-5.5" ,
"choices" : [
{
"index" : 0 ,
"message" : { "role" : "assistant" , "content" : "OpenPAI is a unified API gateway to the major large language models." },
"finish_reason" : "stop"
}
],
"usage" : { "prompt_tokens" : 27 , "completion_tokens" : 19 , "total_tokens" : 46 }
}
Next steps
Top-ups & quota Learn about top-up methods, minimum amounts and invoices.
Models & billing The token / multiplier / cache billing mechanism in detail.
Client integrations Connect tools like Cherry Studio, Cursor and Dify.
Full API reference All endpoint fields, error codes and examples.