GLM 5

GLM 5

zai-org/glm-5
by Z.ai
Documentação da API
Input price
$1/ M tokens
Output price
$3.2/ M tokens
Context window
198Ktokens
Max output
128Ktokens

GLM-5 is an open-source foundation model engineered for complex system engineering and long-horizon Agent tasks, delivering reliable productivity for top-tier programmers. Transcending the boundary from "writing code" to "building systems," it moves beyond traditional snippet generation to offer senior-architect-level planning and execution capabilities. By rejecting the "frontend-heavy, logic-light" approach, GLM-5 demonstrates exceptional reasoning and self-healing abilities in backend refactoring, complex algorithm implementation, and deep debugging—autonomously analyzing logs and iteratively fixing persistent bugs until the system runs. As the first open-source model featuring Opus-class style and system engineering depth, GLM-5 provides extreme logic density alongside the freedom of local deployment and high cost-effectiveness, making it the ideal choice for large-scale backend development and automated Agent construction.

Recursos

API serverless

Documentação

zai-org/glm-5 is available via Novita's serverless API, where you pay per token. There are several ways to call the API, including OpenAI-compatible endpoints with exceptional reasoning performance.

Serverless disponível

Execute consultas imediatamente, pague apenas pelo uso

Entrada$1 / M Tokens
Leitura de cache$0.2 / M Tokens
Saída$3.2 / M Tokens
  1. Obtenha sua chave de API

    Cadastre-se e crie uma chave para executar o código abaixo. A API é compatível com OpenAI.

  2. Make your first request

    The API is OpenAI-compatible: point any OpenAI SDK at the base URL and pass this model ID.

    Base URL
    https://api.novita.ai/openaihttps://api.novita.ai/anthropic
    Model ID
    zai-org/glm-5
    API Endpoint
    chat/completions
    1from openai import OpenAI
    2
    3client = OpenAI(
    4    api_key="<Your API Key>",
    5    base_url="https://api.novita.ai/openai"
    6)
    7
    8response = client.chat.completions.create(
    9    model="zai-org/glm-5",
    10    messages=[
    11        {"role": "system", "content": "You are a helpful assistant."},
    12        {"role": "user", "content": "Hello, how are you?"}
    13    ],
    14    max_tokens=131072,
    15    temperature=0.7
    16)
    17
    18print(response.choices[0].message.content)