Z.ai: GLM 4.5

Public pricingIntelligence 79/100Medium memory深度思考工具调用

Z.ai: GLM 4.5 是一款文本模型，适合智能体工作流与工具调用。它结合了可靠的工具调用与智能体表现、131K tokens上下文和均衡成本定位，可在agent workflows, tool use, and orchestration中提供可靠表现。它适合重视质量、速度与成本的团队，能带来稳定输出、灵活部署与扩展空间。 它适合需要稳定回答、较长上下文、清晰结构和可扩展部署的团队。 它适合需要稳定回答、较长上下文、清晰结构和可扩展部署的团队。 它适合需要稳定回答、较长上下文、清晰结构和可扩展部署的团队。 它适合需要稳定回答、较长上下文、清晰结构和可扩展部署的团队。 它适合需要稳定回答、较长上下文、清晰结构和可扩展部署的团队。 它适合需要稳定回答、较长上下文、清晰结构和可扩展部署的团队。

Input

$0.60/1M

Output

$2.20/1M

Cached

$0.11/1M

Batch

$0.30/1M

Calculate your GLM 4.5 bill.

Set your workload — see cost at your exact volume.

What would GLM 4.5 cost you?

Adjust the workload to see your monthly bill.

1,00010,00050,000250,0001M10M

Technical specifications

GLM 4.5 at a glance.

Memory

131,072

tokens

Max reply

98,304

tokens

Memory tier

Medium

a long report or a codebase file

Tokenizer

—

Released

Jul 2025

Training cutoff

Apr 2025

Availability

Public pricing

Status

active

Benchmarks

Quality benchmarks

Independent evaluations from public leaderboards. Higher is better.

  • aa_intelligence_index

    26

  • aime_2024

    91

  • gpqa_diamond

    79.1

  • humanitys_last_exam

    8.32

  • livecodebench

    72.9

  • math

    98.2

  • mmlu_pro

    84.6

  • swe_bench_verified

    64.2

What it can do

Capabilities & limits.

  • Understands images
  • Deep step-by-step thinking
  • Uses tools / calls functions
  • Strict JSON output
  • Streams replies
  • Fine-tunable on your data

When to pick GLM 4.5

  • Multi-step reasoning, research agents, or hard math.
  • Agentic workflows that call tools or APIs.
  • High-volume workloads where unit cost matters.

When to look elsewhere

  • Your workload involves images — pick a vision-capable model instead.

Alternatives

Similar models to compare.

FAQ

GLM 4.5 — the questions we see most.

Pricing, capabilities, alternatives — generated from the same data that powers the calculator above.

Get instant answers from our AI agent

At a typical workload of 50,000 conversations a month with 1,500-token prompts and 800-token replies, GLM 4.5 costs roughly $133 per month. Input is $0.60 /1M tokens and output is $2.20 /1M tokens.
GLM 4.5 has a 131,072-token context window (medium memory — a long report or a codebase file). That means you can fit about 24,576 words of input and history in a single call.
Beyond text generation, GLM 4.5 supports deep step-by-step reasoning, calling functions / tools, strict JSON output, fine-tuning on your own data. It streams replies by default.
GLM 4.5 was released in July 2025, with training data cut off around April 2025.
Models in a similar class include GLM 4.5V, GLM 5, GLM 4.6. The "Similar models" section below this FAQ links into each.

Still unsure?

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