Chat Completions

The GLM 5 Chat Completions endpoint follows an OpenAI-compatible request and response shape for text chat. Existing OpenAI-compatible clients can usually keep the same SDK and request body, then change the base URL, API key, and model ID.

https://glm5.app/api/v1

Basic Request

curl https://glm5.app/api/v1/chat/completions \
  -H "Authorization: Bearer $GLM5_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "glm-5.3",
    "messages": [
      {"role": "system", "content": "Answer in concise Markdown."},
      {"role": "user", "content": "Explain idempotency in two bullets."}
    ],
    "max_completion_tokens": 600
  }'

Request Body

The request JSON body must be at most 4 MB. GLM 5 does not impose one global token context window across all models. Context and output limits can vary by model, and oversized requests return the corresponding API error.

Supported fields

GLM 5 accepts the documented Chat Completions fields below. Only the documented subset is guaranteed to affect model behavior.

Additional SDK fields

Some SDKs may send fields that are not listed in this reference. GLM 5 may ignore unknown fields for compatibility, but applications should not depend on undocumented behavior.

Notable current limitations include:

• response_format JSON mode and JSON Schema enforcement are not available.
• frequency_penalty, presence_penalty, repetition_penalty, and logit_bias are not applied.
• logprobs and top_logprobs are not returned.
• reasoning and reasoning_effort are not exposed as public controls.
• modalities, audio, and image_config are not supported by this text endpoint.
• stream_options, service_tier, prediction, and parallel_tool_calls are not currently applied.

For strict integrations, only depend on fields documented on this page.

Messages

messages is an ordered array. GLM 5 is stateless: previous turns are only remembered when your application sends them again.

Only text parts are used. Image, audio, video, and file parts are ignored by this text endpoint.

[
  {
    "role": "system",
    "content": "You are a concise technical assistant."
  },
  {
    "role": "user",
    "content": [
      {
        "type": "text",
        "text": "Summarize this deployment checklist."
      }
    ]
  }
]

When trimming history, keep assistant tool_calls and their matching tool messages together. A tool message without a preceding matching tool_call_id returns 400 invalid_request_error.

Non-Streaming Response

Non-streaming calls return a chat.completion object:

{
  "id": "chatcmpl-01...",
  "object": "chat.completion",
  "created": 1785292800,
  "model": "glm-5.3",
  "choices": [
    {
      "index": 0,
      "message": {
        "role": "assistant",
        "content": "- Idempotency makes retries safe..."
      },
      "finish_reason": "stop"
    }
  ],
  "usage": {
    "prompt_tokens": 42,
    "completion_tokens": 31,
    "total_tokens": 73
  }
}

Response Fields

GLM 5 does not currently return fields such as usage.cost, usage.prompt_tokens_details.cached_tokens, service_tier, or system_fingerprint.

Model limits

GLM 5 does not return synthetic context-budget headers or enforce one shared token window for every model. Use the final usage.prompt_tokens value for monitoring and handle any context or output-limit error returned for the selected model.

Finish Reasons

For incremental output, see Streaming. For tool-call loops, see Function calling.