GLM-4.5 API

Advanced version of GLM-4.5 with enhanced capabilities and web search integration

Modalities: TextText
In / Out price: $0.6/$2.2per 1M
Context window: 125K tokens
Released: Sep 9, 2025

GLM-4.5 overview

GLM-4.5 by Zhipu AI

The GLM-4.5 model combines a Mixture-of-Experts architecture and native function calling to provide powerful reasoning and coding.

GLM-4.5 specs

Model ID: zhipu/glm-4.5
Developer: Zhipu AI
Context window: 128,000 tokens
Max output: 98,000 tokens
Input: Text
Output: Text
API: OpenAI-compatible, base URL https://api.aimlapi.com/v1

Zhipu AI's GLM-4.5 is a versatile text-to-text large language model designed for diverse natural language processing tasks. Featuring a 128,000-token context window, it supports understanding and generating very long-form text with high coherence and contextual awareness.

Performance Benchmarks

Optimized for a wide range of text-to-text applications, including complex document understanding, summarization, and generation.

Performance Metrics

GLM-4.5 aims to close the gap by integrating diverse capabilities within a single framework. Across 12 benchmarks spanning agentic tasks (3), reasoning (7), and coding (2), GLM-4.5 achieves an overall third-place ranking. Its variant, GLM-4.5 Air, ranks sixth, showing competitive yet slightly lower results compared to top models from OpenAI, Anthropic, Google DeepMind, xAI, Alibaba, Moonshot, and DeepSeek.

Key Capabilities

Advanced Text Generation: Produces fluent, contextually relevant, and accurate longform text outputs.
Comprehensive Understanding: Strong grasp of semantics allowing for nuanced text manipulations such as summarization, paraphrasing, and dialogue.

Optimal Use Cases

Long-Form Content Creation: Books, reports, and articles requiring deep consistency over many tokens.
Complex Document Analysis: Legal texts, scientific papers, and business documents.
Conversational AI: Chatbots capable of maintaining long context and generating relevant replies.
Text Summarization and Transformation: Effective for generating abstracts, paraphrased content, and multi-turn dialogue synthesis.

Comparison with Other Models

Vs. Claude 4 Sonnet: GLM-4.5 shows close performance in agentic coding and reasoning tasks but still has optimization potential compared to Claude Sonnet 4, which achieves excellent coding success and state-of-the-art reasoning outputs, often favored for autonomous multi-feature app development.

Vs. OpenAI GPT-4.5: GLM-4.5 ranks overall competitive with top models including GPT-4.5 in reasoning and agent benchmarks, though GPT-4.5 generally leads in raw task accuracy on some professional benchmarks like MMLU and AIME.

Vs. Qwen3-Coder and Kimi K2: GLM-4.5 dominates Qwen3-Coder with an 80.8% success rate and wins 53.9% of tasks against Kimi K2, highlighting its superior coding and agentic capabilities for complex programming scenarios.

Vs. Gemini 2.5 Pro: GLM-4.5 holds its ground on reasoning and coding benchmarks but detailed exact percentages are less public; Gemini 2.5 stands stronger in certain coding and reasoning tests but GLM-4.5 balances large context and agentic tools well.

Limitations

The full GLM-4.5 model requires substantial computational resources and GPU memory, potentially limiting deployment feasibility for organizations with constrained infrastructure. The lighter GLM-4.5 Air variant addresses this but with fewer active parameters and slightly reduced capabilities.

Use cases

Long-Form Content Creation: Books, reports, and articles requiring deep consistency over many tokens.
Complex Document Analysis: Legal texts, scientific papers, and business documents.
Conversational AI: Chatbots capable of maintaining long context and generating relevant replies.
Text Summarization and Transformation: Effective for generating abstracts, paraphrased content, and multi-turn dialogue synthesis.

Capabilities

Function calling
Streaming
Structured outputs
Reasoning
Web search

GLM-4.5 benchmarks by Artificial Analysis

See how GLM-4.5 scores on independent evaluations. Data retrieved Nov 3, 2026.

Humanity's Last Exam#180 / 45813%Score GPQA Diamond#148 / 43978.2%Score AA-LCR#207 / 39152.7%Score IFBench#165 / 32544.1%Score

Benchmark results

Compare 12 models available on AI/ML API across 5 independent benchmarks.

Humanity's Last Exam

Expert-written questions across academic subjects.

GLM-4.5 API pricing

GLM-4.5 pricing in US dollars
Usage	Price	Unit
Input	$0.6	1M tokens
Output	$2.2	1M tokens
Cached input	$0.11	1M tokens

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

GLM-4.5 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-4.5	$0.6	$2.2
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-4.5 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-4.5",
  "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-4.5",
    "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-4.5",
    "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-4.5 FAQ

What is the context window of GLM-4.5?

GLM-4.5 has a 128,000 tokens context window and can return up to 98,000 tokens.

What inputs and outputs does GLM-4.5 support?

GLM-4.5 takes text as input and returns text.

What is the model ID for GLM-4.5?

Use zhipu/glm-4.5 as the model id. Requests go to https://api.aimlapi.com/v1/chat/completions.

When was GLM-4.5 released?

GLM-4.5 became available on September 9, 2025.

How much does GLM-4.5 cost?

GLM-4.5 costs $0.6 input and $2.2 output per 1M tokens on AI/ML API, billed as you go with no subscription.

Does GLM-4.5 support streaming?

Yes, GLM-4.5 can stream responses as they are generated.

Who created GLM-4.5?

GLM-4.5 was built by Zhipu AI.

Start building with GLM-4.5

Get API key

GLM-4.5 API

zhipu/glm-4.5

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-4.5",
  "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-4.5",
    "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-4.5",
    "messages": [
      {
        "role": "user",
        "content": "Write a haiku about the ocean."
      }
    ]
  }),
});

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

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GLM-4.5 API

GLM-4.5 overview

GLM-4.5 by Zhipu AI

GLM-4.5 specs

Performance Benchmarks

Performance Metrics

Key Capabilities

Optimal Use Cases

Comparison with Other Models

Limitations

Use cases

Capabilities

GLM-4.5 benchmarks by Artificial Analysis

Benchmark results

Humanity's Last Exam

GPQA Diamond

AA-LCR

IFBench

τ²-Bench Telecom

GLM-4.5 API pricing

GLM-4.5 vs other models: token prices

How to use the GLM-4.5 API

Build with your agent

1Get your API key

2Make your first request

Related articles

GLM-4.5 FAQ

Start building with GLM-4.5

GLM-4.5 API

Build with your agent

1Get your API key

2Make your first request

GLM-4.5 API

GLM-4.5 overview

GLM-4.5 by Zhipu AI

GLM-4.5 specs

Performance Benchmarks

Performance Metrics

Key Capabilities

Optimal Use Cases

Comparison with Other Models

Limitations

Use cases

Capabilities

Benchmark results

Humanity's Last Exam

GPQA Diamond

AA-LCR

IFBench

τ²-Bench Telecom

GLM-4.5 API pricing

GLM-4.5 vs other models: token prices

How to use the GLM-4.5 API

Build with your agent

1Get your API key

2Make your first request

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