Create a chat completion

The OpenAI Chat Completions endpoint. Every key group that serves text models can call it, including chat-only groups (DeepSeek, GLM platforms). On chat-only groups the body goes to the provider unchanged; on other groups it is converted and some fields are dropped (see Notes below).

#Request

POST https://bigmodel.io/v1/chat/completions

#Authentication

Send one of these.

#Body

Standard OpenAI Chat Completions body. For GLM, DeepSeek and Qwen groups the body is passed to the provider as is (only model is rewritten), so support for each field depends on the model. Other groups convert the request, and response_format, n, seed, user and logprobs are dropped there.

#Response

#Response fields

With stream: true the response is a server-sent event stream of chat.completion.chunk objects ending with data: [DONE]. The gateway asks the upstream for a final usage chunk.

#Examples

curl https://bigmodel.io/v1/chat/completions \
  -H "Authorization: Bearer $BIGMODEL_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "glm-5.3",
    "messages": [
      {"role": "system", "content": "You are a concise assistant."},
      {"role": "user", "content": "Explain HTTP 429 in one sentence."}
    ],
    "max_tokens": 128
  }'

import os
from openai import OpenAI

client = OpenAI(base_url="https://bigmodel.io/v1", api_key=os.environ["BIGMODEL_API_KEY"])

resp = client.chat.completions.create(
    model="glm-5.3",
    messages=[
        {"role": "system", "content": "You are a concise assistant."},
        {"role": "user", "content": "Explain HTTP 429 in one sentence."},
    ],
    max_tokens=128,
)
print(resp.choices[0].message.content)

import OpenAI from 'openai'

const client = new OpenAI({baseURL: 'https://bigmodel.io/v1', apiKey: process.env.BIGMODEL_API_KEY})

const resp = await client.chat.completions.create({
  model: 'glm-5.3',
  messages: [
    {role: 'system', content: 'You are a concise assistant.'},
    {role: 'user', content: 'Explain HTTP 429 in one sentence.'},
  ],
  max_tokens: 128,
})
console.log(resp.choices[0].message.content)

Example response (the id, timestamps, text and token counts are illustrative; extra fields such as reasoning_content come from the model provider):

{
  "id": "chatcmpl-...",
  "object": "chat.completion",
  "created": 1792310400,
  "model": "glm-5.3",
  "choices": [
    {
      "index": 0,
      "message": {"role": "assistant", "content": "HTTP 429 means you sent too many requests in a given time and should retry later."},
      "finish_reason": "stop"
    }
  ],
  "usage": {"prompt_tokens": 24, "completion_tokens": 19, "total_tokens": 43}
}

#Streaming

curl -N https://bigmodel.io/v1/chat/completions \
  -H "Authorization: Bearer $BIGMODEL_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"model":"glm-5.3","stream":true,"messages":[{"role":"user","content":"Count to 3."}]}'

stream = client.chat.completions.create(
    model="glm-5.3",
    messages=[{"role": "user", "content": "Count to 3."}],
    stream=True,
)
for chunk in stream:
    if chunk.choices and chunk.choices[0].delta.content:
        print(chunk.choices[0].delta.content, end="", flush=True)

const stream = await client.chat.completions.create({
  model: 'glm-5.3',
  messages: [{role: 'user', content: 'Count to 3.'}],
  stream: true,
})
for await (const chunk of stream) process.stdout.write(chunk.choices[0]?.delta?.content ?? '')

The stream ends with data: [DONE]. The last data chunk usually carries usage and an empty choices array, so skip chunks without choices, as above.

#Fallback models

{
  "model": "glm-5.3",
  "models": ["kimi-k3", "deepseek-v4-pro"],
  "messages": [{"role": "user", "content": "Hello"}]
}

The gateway tries glm-5.3, then the models entries in order. See OpenRouter compatibility.

#Notes

• Field support depends on the group. On chat-only groups (DeepSeek, GLM platforms) only model is rewritten; tools, tool_choice, response_format, thinking, reasoning_effort and image input pass through, and support depends on the model. On other OpenAI groups and on Anthropic groups the request is converted, and only model, messages, instructions, max_tokens, max_completion_tokens, temperature, top_p, stream, stream_options.include_usage, tools, tool_choice, reasoning_effort, service_tier, stop, functions and function_call survive. response_format, n, seed, user and logprobs are dropped on those paths, so JSON mode is not enforced there. See Structured output.
• Unknown model → 503, not 404. A model your group does not serve, or a typo, returns 503 api_error "No available accounts: no available accounts supporting model: …". Copy IDs from /models or GET /v1/models.
• OpenRouter-style requests. z-ai/glm-5.3 and suffixes like :nitro are resolved to a served model where possible; :free is never stripped. models allows at most 5 attempts in total; fallback happens on 404, 408, 429 and 5xx before any bytes are sent, never on 400/401/402/403/413. You pay only for the attempt that succeeds. provider, transforms and route are ignored.
• Streaming usage. The gateway always requests usage from the upstream, so the final chunk has token counts even if you did not set stream_options. Errors after the stream starts arrive as an SSE error event.
• Bad JSON, an empty body or a missing model returns 400 invalid_request_error.
• Full error list: Errors.

#Related

• Streaming
• Tool calling
• Image input
• OpenAI SDK