Model facet · API

GLM-5.3 API quickstart

GLM-5.3 exposes three request protocols — OpenAI Chat Completions, OpenAI Responses, and Anthropic Messages — so most existing SDKs and coding tools can point at it with a base URL change. This page is a quickstart; the full step-by-step guides cover individual tools and operating parameters in depth.

Three request protocols

ProtocolUse whenBase path
OpenAI Chat CompletionsMost existing OpenAI-SDK integrations and coding toolsView
OpenAI ResponsesNewer OpenAI-SDK tool-use and structured-output flowsView
Anthropic MessagesClaude Code and other Anthropic-SDK-based toolsView

Minimal request

Example
curl https://api.oneinfer.ai/v1/ula/chat/completions \
  -H "Authorization: Bearer $ONEINFER_TOKEN" \
  -H "Content-Type: application/json" \
  -d '{"model":"glm-5.3","messages":[{"role":"user","content":"Reply with: connection verified"}],"reasoning_effort":"low"}'

Reasoning is mandatory, not optional

GLM-5.3 cannot fully disable reasoning. Set reasoning_effort explicitly (low, high, or max) rather than relying on a default — it is the single biggest lever on latency and cost.

Ready to test the workflow?

Create account & add credits

Go deeper

  • Full setup and troubleshooting for a specific key or tool — see the integration guides.
  • Choosing an effort level per task — see the reasoning-effort guide.
  • Defining tools and validating structured output — see the function-calling guide.

Frequently asked questions

How do I use GLM-5.3 with the API?

Send an OpenAI- or Anthropic-compatible request with model "glm-5.3", a valid API key, and an explicit reasoning_effort of low, high, or max.

Where is the live GLM-5.3 model page?

The canonical model page with current OneInfer pricing, capabilities, and availability is /models/zai-org/GLM-5.3. This page is a focused facet of that entity, not a replacement for it.

How should I treat benchmark or price claims?

Check each claim’s provenance label and observed date. Vendor-reported and independently verified numbers are shown as separate evidence classes on this hub.

Put GLM-5.3 to work

Fund a controlled evaluation, start with a prepared prompt, and measure quality and cost on your own workload.