GLM-5.2 API

GLM-5.2 is Zhipu AI flagship MoE LLM with a 1M-token context window, optimized for agentic coding, tool use, reasoning, and long-context tasks.

Modalities: TextText
In / Out price: $1.4/$4.4per 1M
Context window: 1M tokens
Released: Jun 16, 2026

GLM-5.2 overview

GLM-5.2 by Zhipu AI

GLM-5.2 is an advanced AI model with a 1M-token context window, agentic coding capabilities, long-horizon reasoning, and repo-scale analysis.

GLM-5.2 specs

Model ID: zhipu/glm-5.2
Developer: Zhipu AI
Context window: 1,000,000 tokens
Max output: 131,072 tokens
Input: Text
Output: Text
API: OpenAI-compatible, base URL https://api.aimlapi.com/v1

What Is GLM-5.2 API?

GLM-5.2 is Z.ai's latest flagship AI model, purpose-built for advanced coding, autonomous software development, and complex reasoning tasks. As the newest member of the GLM series, it introduces a massive 1 million-token context window, enabling deeper project understanding and more effective long-term task execution.

Technical Reference

Developer	Z.ai (Zhipu AI)
Model ID	glm-5.2 glm-5.2[1m]
Release Date	June 13, 2026
Context Window (default)	202,752 tokens (~203K)
Context Window (extended)	1,000,000 tokens, use glm-5.2[1m] model ID
Max Output Tokens	131,072
Architecture (family)	MoE (Mixture of Experts), 744B total parameters in GLM-5 base
Training Hardware	Huawei Ascend (non-NVIDIA)
Training Algorithm	Asynchronous Agent RL for long-chain stability
Thinking Modes	High Max (effort switchable via /effort in Claude Code)
Modalities	Text (input and output)
Languages Evaluated	9+ programming languages across 10,000+ test environments

What GLM-5.2 Actually Does Differently

The headline is the context window, but that number is only meaningful if the model can actually use it. Here's what distinguishes GLM-5.2 from both its predecessors and the wider field of coding-focused models.

One-million-token usable context

Z.ai specifically qualifies this as "usable", not just formally accepted. The model is designed to maintain coherent understanding across the full length, which matters when you drop an entire monorepo in at once. That's a 5× jump from GLM-5.1's 200K window.

Asynchronous Agent Reinforcement Learning

A new training algorithm developed specifically for stability on long reasoning and action chains. Where models can drift or lose track of earlier context in extended agentic sessions, the async RL approach is designed to keep execution coherent over hundreds of tool calls.

Two-tier thinking modes

GLM-5.2 simplifies effort control to two modes: High and Max. Standard tasks default to High; for the most complex refactors and architecture decisions, Max unlocks deeper reasoning. Z.ai recommends Max for demanding coding work.

Use cases

GLM-5.2 is documented as suited for long-horizon autonomous coding and engineering tasks, including completing a full development workflow from requirements to multi-platform deployment in one task.

It is also suited for cross-file, multi-step, long-chain software work such as testing module decoupling, interface migration, directory cleanup, SDK adaptation, and cross-language refactoring.

The model is documented for mobile app development scenarios, where it can cover client architecture, streaming messages, long connections, local state management, keyboard behavior, scrolling logic, system notifications, permissions, and background recovery.

It is also documented for small-program development, including page subdivision, custom components, page stack management, request wrapping, authentication state maintenance, lifecycle management, and handling abnormal states.

Capabilities

Reasoning
Structured outputs

GLM-5.2 benchmarks by Artificial Analysis

See how GLM-5.2 compares in generation speed and latency. Data retrieved Nov 3, 2026.

Speed#124 / 21988.2Output tokens / second Latency#123 / 2161.73Seconds to first token Humanity's Last Exam#44 / 45841.1%Score GPQA Diamond#49 / 43989.5%Score

Speed

Output tokens / second

Benchmark results

Compare 11 models available on AI/ML API across 5 independent benchmarks.

Humanity's Last Exam

Expert-written questions across academic subjects.

GLM-5.2 API pricing

GLM-5.2 pricing in US dollars
Usage	Price	Unit
Input	$1.4	1M tokens
Output	$4.4	1M tokens
Cached input	$0.26	1M tokens

Prices from the AI/ML API price list, checked on Nov 4, 2026.

GLM-5.2 vs other models: token prices

AI/ML API input and output rates for 5 models, per million tokens.

AI/ML API model prices in USD per million tokens
Model	Input	Output
GLM-5.2	$1.4	$4.4
GLM-5.3-Flash	$0.15	$0.5
GLM 5.3 FlashX	$0.37	$1.25
GLM-5.3	$1.4	$4.4
GLM 5.2 Fast Preview	$3.5	$11

How to use the GLM-5.2 API

View docs

Build with your agent

Give your agent the model details, code and documentation.

1Get your API key

Create API key

export AIMLAPI_KEY="8f2b4c7d9a1e6b3f…"

2Make your first request

curl 'https://api.aimlapi.com/v1/chat/completions' \
  -H "Authorization: Bearer $AIMLAPI_KEY" \
  -H 'Content-Type: application/json' \
  -d '{
  "model": "zhipu/glm-5.2",
  "messages": [
    {
      "role": "user",
      "content": "Write a haiku about the ocean."
    }
  ]
}'

import os
import requests

headers = {
    "Authorization": f"Bearer {os.environ['AIMLAPI_KEY']}",
    "Content-Type": "application/json",
}
payload = {
    "model": "zhipu/glm-5.2",
    "messages": [
        {
            "role": "user",
            "content": "Write a haiku about the ocean."
        }
    ]
}

response = requests.post("https://api.aimlapi.com/v1/chat/completions", headers=headers, json=payload, timeout=120)
response.raise_for_status()
print(response.json())

const response = await fetch("https://api.aimlapi.com/v1/chat/completions", {
  method: "POST",
  headers: {
    Authorization: `Bearer ${process.env.AIMLAPI_KEY}`,
    "Content-Type": "application/json",
  },
  body: JSON.stringify({
    "model": "zhipu/glm-5.2",
    "messages": [
      {
        "role": "user",
        "content": "Write a haiku about the ocean."
      }
    ]
  }),
});

if (!response.ok) throw new Error(`HTTP ${response.status}`);
console.log(await response.json());

All posts

GLM-5.2 FAQ

What is the context window of GLM-5.2?

GLM-5.2 has a 1,000,000 tokens context window and can return up to 131,072 tokens.

What inputs and outputs does GLM-5.2 support?

GLM-5.2 takes text as input and returns text.

What is the model ID for GLM-5.2?

Use zhipu/glm-5.2 as the model id. Requests go to https://api.aimlapi.com/v1/chat/completions.

When was GLM-5.2 released?

GLM-5.2 became available on June 16, 2026.

How much does GLM-5.2 cost?

GLM-5.2 costs $1.4 input and $4.4 output per 1M tokens on AI/ML API, billed as you go with no subscription.

Does GLM-5.2 support streaming?

Yes, GLM-5.2 can stream responses as they are generated.

Who created GLM-5.2?

GLM-5.2 was built by Zhipu AI.

Start building with GLM-5.2

Get API key

GLM-5.2 API

zhipu/glm-5.2

Build with your agent

Give your agent the model details, code and documentation.

1Get your API key

Create API key

export AIMLAPI_KEY="8f2b4c7d9a1e6b3f…"

2Make your first request

curl 'https://api.aimlapi.com/v1/chat/completions' \
  -H "Authorization: Bearer $AIMLAPI_KEY" \
  -H 'Content-Type: application/json' \
  -d '{
  "model": "zhipu/glm-5.2",
  "messages": [
    {
      "role": "user",
      "content": "Write a haiku about the ocean."
    }
  ]
}'

import os
import requests

headers = {
    "Authorization": f"Bearer {os.environ['AIMLAPI_KEY']}",
    "Content-Type": "application/json",
}
payload = {
    "model": "zhipu/glm-5.2",
    "messages": [
        {
            "role": "user",
            "content": "Write a haiku about the ocean."
        }
    ]
}

response = requests.post("https://api.aimlapi.com/v1/chat/completions", headers=headers, json=payload, timeout=120)
response.raise_for_status()
print(response.json())

const response = await fetch("https://api.aimlapi.com/v1/chat/completions", {
  method: "POST",
  headers: {
    Authorization: `Bearer ${process.env.AIMLAPI_KEY}`,
    "Content-Type": "application/json",
  },
  body: JSON.stringify({
    "model": "zhipu/glm-5.2",
    "messages": [
      {
        "role": "user",
        "content": "Write a haiku about the ocean."
      }
    ]
  }),
});

if (!response.ok) throw new Error(`HTTP ${response.status}`);
console.log(await response.json());

Docs for AI agents Plain-text index · llms.txt API documentation API reference and examples

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GLM-5.2 API

GLM-5.2 overview

GLM-5.2 by Zhipu AI

GLM-5.2 specs

What Is GLM-5.2 API?

Technical Reference

What GLM-5.2 Actually Does Differently

One-million-token usable context

Asynchronous Agent Reinforcement Learning

Two-tier thinking modes

Use cases

Capabilities

GLM-5.2 benchmarks by Artificial Analysis

Speed

Benchmark results

Humanity's Last Exam

GPQA Diamond

Terminal-Bench 4.0

AA-LCR

SciCode

GLM-5.2 API pricing

GLM-5.2 vs other models: token prices

How to use the GLM-5.2 API

Build with your agent

1Get your API key

2Make your first request

Related articles

GLM-5.2 FAQ

Start building with GLM-5.2

GLM-5.2 API

Build with your agent

1Get your API key

2Make your first request

GLM-5.2 API

GLM-5.2 overview

GLM-5.2 by Zhipu AI

GLM-5.2 specs

What Is GLM-5.2 API?

Technical Reference

What GLM-5.2 Actually Does Differently

One-million-token usable context

Asynchronous Agent Reinforcement Learning

Two-tier thinking modes

Use cases

Capabilities

Speed

Benchmark results

Humanity's Last Exam

GPQA Diamond

Terminal-Bench 4.0

AA-LCR

SciCode

GLM-5.2 API pricing

GLM-5.2 vs other models: token prices

How to use the GLM-5.2 API

Build with your agent

1Get your API key

2Make your first request

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