Start calling this model with endpoint-specific examples.
Headline benchmark standings and comparison context.
Key dates, capabilities, and model metadata.
Start calling this model with endpoint-specific examples.
Headline benchmark standings and comparison context.
Key dates, capabilities, and model metadata.
Start calling this model with endpoint-specific examples.
Headline benchmark standings and comparison context.
Key dates, capabilities, and model metadata.
15 Apr 2025
15 Apr 2025
License
MIT
Input
No modalities listed.
Output
No modalities listed.
Core latency and throughput trends from recent traffic.
Start calling this model with endpoint-specific examples.
Choose a supported endpoint, pick a main language, then select the example style you want to copy.
import AIStats from '@ai-stats/sdk';
const client = new AIStats({
apiKey: process.env.AI_STATS_API_KEY,
});
const response = await client.generateResponse({
"model": "z-ai/glm-4-32b",
"input": "Give me one fun fact about cURL.",
"service_tier": "standard"
});
const outputText = response.output
?.flatMap((item) => item.content ?? [])
.find((item) => item.type === "output_text")
?.text;
console.log(outputText ?? response);Parameters
Aggregated across active providers for the responses route.
Routing will select a compatible provider when a parameter narrows availability, so this list stays model-facing instead of provider-facing.
| Parameter | Description |
|---|---|
temperature | Controls how random token selection can be. |
top_p | Applies nucleus sampling by limiting candidates to a probability mass threshold. |
max_tokens | Caps output length on endpoints and providers that use the max_tokens field name. |
tool_choice | Controls which tool, if any, the model should call. |
tools | Defines callable tools or functions the model can invoke. |
Select a route to update the request snippet and compatibility details.
/v1/responses/v1/chat/completions/v1/messagesLatency
Throughput
Uptime