Z.ai: GLM 4.5

Public pricingIntelligence 79/100Medium memoryगहरी सोचटूल उपयोग

Z.ai: GLM 4.5 एक टेक्स्ट मॉडल है, जिसे agent workflows और tool use के लिए बनाया गया है। यह विश्वसनीय tool use और agent behavior, 131K tokens का context और संतुलित लागत profile जोड़कर agent workflows, tool use, and orchestration में भरोसेमंद काम करता है। यह तब व्यावहारिक विकल्प है जब गुणवत्ता, गति और लागत महत्वपूर्ण हो, खासकर उन टीमों के लिए जिन्हें स्थिर output,

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.

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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