Z.ai: GLM 4.5

Public pricingIntelligence 79/100Medium memoryDeep thinkingTool use

Z.ai: GLM 4.5 is a text model for agent workflows and tool use. It combines reliable tool use and agent behavior with a 131K tokens context window and a balanced-cost profile. Use it for agent workflows, tool use, and orchestration when quality, speed, and cost matters. It is a practical choice for teams that need reliable output, flexible deployment, and room to scale.

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?

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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.

  • mmlu_pro

    84.6
  • gpqa_diamond

    79.1
  • swe_bench_verified

    64.2
  • math

    98.2
  • aime_2024

    91
  • livecodebench

    72.9
  • aa_intelligence_index

    26
  • humanitys_last_exam

    8.32

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.

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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