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Z.AIChat

GLM 5V Turbo

glm-5v-turbo

GLM-5V-Turbo is Z.ai's first native multimodal agent foundation model, designed for vision-based coding and agent-driven workflows. It natively supports image, video, and text inputs, enabling integrated multimodal reasoning and execution. The model excels at long-horizon planning, complex coding, and multi-step task execution, and works seamlessly with agents to complete the full loop of “perceive → plan → execute”, making it well suited for advanced multimodal automation and real-world agent systems.

Context
202.8K tokens
Endpoint
Get API KeyCompare

Pricing

Input$1.20 / 1M
Output$4.00 / 1M
Cache Write (5m)Not published
Cache Write (1h)Not published
Cache ReadNot published
Web Search$0 / 1M

Quick Start

Select an endpoint and copy a working example for this model.

Endpoint:
python
from openai import OpenAI client = OpenAI(    api_key="YOUR_API_KEY",    base_url="https://api.apertis.ai/v1") response = client.chat.completions.create(    model="glm-5v-turbo",    messages=[        {"role": "user", "content": "Hello!"}    ],    max_tokens=1024,    temperature=0.7) print(response.choices[0].message.content) # Optional: Enable context compression to reduce token usage# response = client.chat.completions.create(#     model="glm-5v-turbo",#     messages=[{"role": "user", "content": "Hello!"}],#     extra_body={"compression": {"enabled": True, "model": "gpt-4.1-mini"}}# )

Supported Parameters

API docs
Common7 params
modelmessagesmax_tokenstemperaturetop_pstreamtools
Extended4 params
reasoning_effortstream_optionsthinkingextra_body

Cursor IDE Model IDs

Use these namespaced identifiers in Cursor IDE to avoid conflicts with built-in models.

glm-5v-turbo

Decision guidance

Fit the request contract before production.

Coding-agent gateway guide

Use this model when

  • The workload includes code generation or code-oriented text tasks listed in the current catalog record.
  • The required task matches the listed capabilities: text-to-text, text-to-code, translation.
  • The request depends on listed features such as vision, thinking, function-calling.
  • The input fits within the published 202.8K-token context record, with output and system overhead budgeted separately.

Check before production

  • Confirm the production client uses one of the listed request surfaces: /v1/chat/completions, /v1/responses, /v1/messages.
  • Estimate a representative request from the current Pay As You Go price fields instead of extrapolating from a tiny prompt.
  • Check the observed-availability card and run your own timeout, retry, and fallback test before relying on the model.

Compare with Other Models

See how this model compares to others from the same provider.

GLM 5.3

GLM-5.3 is Z.ai's large-scale reasoning model designed for complex software engineering and long-horizon agentic workflows. It supports text input and output with a 1M-token context window, enabling sustained reasoning across large codebases and extended multi-step tasks. Building on GLM-5.2, it delivers stronger coding performance while improving the balance between capability and token efficiency, making it well suited for autonomous coding agents, large-scale engineering workflows, and complex task execution.

Context
1M
Input
$1.40/M
Output
$4.40/M

GLM-4.7 (Thinking)

GLM-4.7 is Z.AI's newest flagship model, upgraded for stronger programming performance and more reliable multi-step reasoning. It handles complex agent tasks better while offering smoother conversations and improved UI/experience quality.

Context
202.8K
Input
$0.30/M
Output
$0.50/M

GLM 4.6 (Thinking)

GLM-4.6 improves on GLM-4.5 with a larger 200K context window, stronger coding performance (including better real-world agent tools like Claude Code and Cline), and clearer gains in reasoning with built-in tool use. It delivers more capable agent behavior, integrates better into agent frameworks, and produces more natural, readable writing — especially in role-playing scenarios.

Context
202.8K
Input
$0.40/M
Output
$1.50/M

GLM 4.7 Flash

GLM-4.7-Flash is a state-of-the-art 30B-class model designed to strike a strong balance between performance and efficiency. It is specifically optimized for agentic coding scenarios, with enhanced capabilities in code generation, long-horizon task planning, and tool-based collaboration. Among open-source models of comparable size, GLM-4.7-Flash has achieved leading results on multiple public benchmark leaderboards, establishing itself as a competitive and practical choice for advanced developer and agent workflows.

Context
200K
Input
$0.06/M
Output
$0.40/M