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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)$1.20 / 1M
Cache Write (1h)$1.20 / 1M
Cache Read$1.20 / 1M
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

Compare with Other Models

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

GLM 5.3 Flash

GLM-5.3-Flash is Z.AI's efficient native multimodal model, designed for coding and long-horizon agentic workflows. It combines strong multimodal capabilities with an architecture optimized for responsive, cost-efficient task execution. Built on a hybrid sparse and linear attention architecture, GLM-5.3-Flash maintains accurate long-context behavior while reducing computational overhead, making it well suited for coding agents, extended multi-step tasks, and scalable production workloads.

Context
1M
Input
$0.075/M
Output
$0.25/M

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
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Input
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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
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Input
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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