BigModel (Zhipu AI)

Use bigmodel/ for the domestic BigModel platform and zai/ for international Z.AI. Each platform uses its own credentials and default URL

model_list:
  - model_name: glm
    litellm_params:
      model: bigmodel/glm-5.3
      api_key: os.environ/BIGMODEL_API_KEY
      api_base: https://open.bigmodel.cn

One model configuration supports all three native APIs. The provider selects the upstream endpoint from the requested API

Proxy endpoint	BigModel endpoint
`/v1/chat/completions`	`/api/paas/v4/chat/completions`
`/v1/responses`	`/api/v1/responses`
`/v1/messages`	`/api/anthropic/v1/messages`

api_base is optional and defaults to https://open.bigmodel.cn. Set BIGMODEL_API_BASE to override the default, or pass an explicit api_base to override the environment value. Existing API-specific base URLs and complete endpoint URLs are normalized, preserving a custom proxy's path prefix

The Admin UI lists BigModel (Zhipu AI), displays its official logo, and provides a required password API Key field and an optional API Base field with the default URL. Authentication uses an explicit api_key or BIGMODEL_API_KEY

import litellm

chat = litellm.completion(
    model="bigmodel/glm-5.3",
    messages=[{"role": "user", "content": "Hello"}],
    thinking={"type": "enabled"},
    reasoning_effort="low",
)

response = litellm.responses(
    model="bigmodel/glm-5.3",
    input="Hello",
    reasoning={"effort": "low"},
    store=True,
)

async def messages():
    return await litellm.anthropic.messages.acreate(
        model="bigmodel/glm-5.3",
        max_tokens=1024,
        messages=[{"role": "user", "content": "Hello"}],
        thinking={"type": "adaptive"},
        output_config={"effort": "low"},
    )

Each API retains its native response format and streaming events. The native Messages SDK entry point is asynchronous, as is the proxy's /v1/messages route

GLM-5.3, GLM-5.3-Flash, and GLM-5.3-FlashX use always-on thinking. GLM-5.3 supports low, high, and max reasoning effort. Messages preserves native thinking, output_config, and reasoning_effort parameters

Set store=True when creating a Responses request if you need continuation, retrieval, or deletion. Use the response ID returned by LiteLLM. BigModel documents a seven-day retention period and does not support cancel, compact, native WebSocket, or file_search

Codex sends include and parallel_tool_calls on every Responses request, and LiteLLM does not forward either to BigModel. Set drop_params: true on the deployment so LiteLLM drops them instead of answering 400

The model catalog and packaged backup include GLM-5.3, GLM-5.3-Flash, and GLM-5.3-FlashX. Prices are expressed in USD/token using a static 7.0 CNY/USD conversion, with the source and verification date in each entry's metadata. Use existing litellm_params cost fields for contract-specific deployment prices

API references: Chat Completions, Responses, Messages, and pricing, checked on 2026-10-27

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BigModel (Zhipu AI)

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