Zhipu GLM-5.2 — a frontier bilingual (Chinese/English) model for reasoning, coding, and agent workflows.

Model:
USD estimate $0.002-$0.004: highest recharge package uses $1 = 2,000 credits; entry package uses $1 = 1,000 credits.

History
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0 running · 0 completed
Input
≈ $0.0009-$0.0018
Output
≈ $0.0044-$0.0088
Cache
≈ $0.0004-$0.0008
Context
Max output
API Reference
Call this model through a standard REST API. Authenticate with your API key, then pick an endpoint below to see its parameters and examples.
Authentication
Every request needs a Bearer token in the Authorization header. Create an API key in the console.
Authorization: Bearer YOUR_API_KEYhttps://apiany.ai/v1/chat/completionsRequest parameters
| Parameter | Type | Required | Notes |
|---|---|---|---|
model | string | Required | Model identifier to invoke. Use this model's ID. |
messages | array | Required | Conversation history in OpenAI chat format (role + content). |
stream | boolean | Optional | When true, the response streams back as server-sent events. |
Request example
curl "https://apiany.ai/v1/chat/completions" \
-H "Authorization: Bearer YOUR_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"model": "glm-5.2",
"messages": [
{
"role": "user",
"content": "Summarize APIAny's multi-channel model aggregation in three sentences, and give one production-ready recommendation."
}
],
"temperature": 0.2,
"max_tokens": 400
}'Response example
{
"id": "chatcmpl-abc123",
"object": "chat.completion",
"model": "glm-5.2",
"choices": [
{
"index": 0,
"message": {
"role": "assistant",
"content": "Hello! How can I help?"
},
"finish_reason": "stop"
}
],
"usage": {
"prompt_tokens": 12,
"completion_tokens": 18,
"total_tokens": 30
}
}