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Zhipu AI model product

GLM 4.5

GLM-4.5 is an Agentic, Reasoning, and Coding (ARC) foundation model designed for intelligent agents, featuring 355 billion total parameters with 32 billion active parameters using MoE architecture. Trained on 23T tokens through multi-stage training, it is a hybrid reasoning model that provides two modes: thinking mode for complex reasoning and tool usage, and non-thinking mode for immediate responses. The model unifies agentic, reasoning, and coding capabilities with 128K context length support. It achieves exceptional performance with a score of 63.2 across 12 industry-standard benchmarks, placing 3rd among all proprietary and open-source models. Released under MIT open-source license allowing commercial use and secondary development.

Updated Aug 10, 2026. Default version: GLM-4.5

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LLMBoard score62.0GLM-4.5
Coverage100%8 benchmark families
Context window131.1KTokens
Official input priceN/AOfficial price unavailable

On this page

  • Specification
  • Capability
  • Benchmarks
  • Arena
  • Pricing
  • Versions
  • About
  • Compare
  • Similar models
  • FAQ

Model specification

Structured fields from the published default version.

Version
GLM-4.5
Released
Jul 28, 2025
Knowledge cutoff
Apr 1, 2025
Parameters
355B
Context window
131.1K
Max output
98.3K
Inputs
text
Outputs
text
Open weights
Yes
License
MIT

Capability profile

This profile uses the latest version under this unique model that has a calculated LLMBoard score. Arena and price are excluded.

GLM-4.5 category scores

Benchmark results

Published benchmark records for the scored version GLM-4.5.

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Columns

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AA-Index0.713100.0%CAug 7, 2026
BFCL-v30.8119100.0%CAug 7, 2026
MATH-5001.033293.5%CAug 7, 2026
TAU-bench Airline0.642386.4%CAug 7, 2026
TAU-bench Retail0.862579.2%CAug 7, 2026
AIME 20240.985386.5%CAug 7, 2026
SciCode0.4111841.2%CAug 7, 2026
Terminal-Bench0.4122554.2%CAug 7, 2026
LiveCodeBench0.7187376.4%CAug 7, 2026
MMLU-Pro0.82312982.8%CAug 7, 2026
BrowseComp0.356583.5%CAug 7, 2026
Humanity's Last Exam0.1739220.9%CAug 7, 2026
SWE-Bench Verified0.67410429.1%CAug 7, 2026
GPQA0.89023361.6%CAug 7, 2026

Arena results

Preference and agent-evaluation signals from published Arena datasets.

58 rows
Columns

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textjapanese411417.1707N/AAug 6, 2026
textspanish461450.4623N/AAug 6, 2026
textindustry medicine and healthcare481454.41,379N/AAug 6, 2026
textindustry entertainment and sports and media661405.34,317N/AAug 6, 2026
text style controljapanese721394.0707N/AAug 6, 2026
textindustry legal and government741437.91,485N/AAug 6, 2026
textnon english741419.012,836N/AAug 6, 2026
textoverall771429.124,269N/AAug 6, 2026
textchinese771469.21,343N/AAug 6, 2026
textexclude ties781421.217,311N/AAug 6, 2026
textindustry life and physical and social science781443.03,872N/AAug 6, 2026
textpolish781420.31,640N/AAug 6, 2026
textkorean801376.3606N/AAug 6, 2026
text style controlspanish821427.2623N/AAug 6, 2026
textindustry business and management and financial operations831420.04,276N/AAug 6, 2026
textmath861427.41,420N/AAug 6, 2026
textcreative writing891395.43,120N/AAug 6, 2026
textrussian911415.61,247N/AAug 6, 2026
textenglish921433.611,421N/AAug 6, 2026
textindustry writing and literature and language921402.65,350N/AAug 6, 2026
texthard prompts931429.211,188N/AAug 6, 2026
textexpert941427.91,102N/AAug 6, 2026
textindustry mathematical951426.91,256N/AAug 6, 2026
textfrench961427.5305N/AAug 6, 2026
textindustry software and it services971438.88,265N/AAug 6, 2026
textinstruction following971403.76,163N/AAug 6, 2026
textgerman1011405.1519N/AAug 6, 2026
textmulti turn1031416.63,900N/AAug 6, 2026
textlonger query1041411.14,998N/AAug 6, 2026
textcoding1061433.54,765N/AAug 6, 2026
text style controlexpert1091438.81,102N/AAug 6, 2026
texthard prompts english1101424.85,687N/AAug 6, 2026
text style controlinstruction following1141404.56,163N/AAug 6, 2026
text style controlkorean1151348.4606N/AAug 6, 2026
text style controlmath1151412.71,420N/AAug 6, 2026
text style controlindustry medicine and healthcare1161434.61,379N/AAug 6, 2026
text style controlindustry entertainment and sports and media1171383.54,317N/AAug 6, 2026
text style controlindustry mathematical1171417.11,256N/AAug 6, 2026
text style controlhard prompts1181432.811,188N/AAug 6, 2026
text style controlindustry business and management and financial operations1191411.44,276N/AAug 6, 2026
text style controlindustry software and it services1231443.58,265N/AAug 6, 2026
text style controlnon english1241396.812,836N/AAug 6, 2026
text style controloverall1251410.824,269N/AAug 6, 2026
text style controlexclude ties1251396.817,311N/AAug 6, 2026
text style controlindustry legal and government1261416.01,485N/AAug 6, 2026
text style controlcoding1271454.34,765N/AAug 6, 2026
text style controlfrench1271417.4305N/AAug 6, 2026
text style controllonger query1271416.14,998N/AAug 6, 2026
text style controlpolish1271383.21,640N/AAug 6, 2026
text style controlchinese1281438.51,343N/AAug 6, 2026
text style controlenglish1281419.411,421N/AAug 6, 2026
text style controlhard prompts english1301432.35,687N/AAug 6, 2026
text style controlindustry life and physical and social science1301422.23,872N/AAug 6, 2026
text style controlindustry writing and literature and language1301382.95,350N/AAug 6, 2026
text style controlmulti turn1311406.03,900N/AAug 6, 2026
text style controlrussian1311395.91,247N/AAug 6, 2026
text style controlcreative writing1321373.23,120N/AAug 6, 2026
text style controlgerman1391375.7519N/AAug 6, 2026

Pricing

Official vendor API PAYG pricing is summarized first. The table then lists individual provider offerings without treating their minimum as the official price.

Official API
N/A
Official provider
N/A
Lowest third-party
From $0.286 input, $1.14 output per 1M via 302.AI
Tracked offerings
4
3 rows
Columns

Show columns

302.AIglm-4.5global$0.286$1.14131.1KAug 7, 2026
LLM Gatewayglm-4.5global$0.60$2.2131KAug 7, 2026
Z.AIglm-4.5global$0.60$2.2131.1KAug 7, 2026

Official prices use only the vendor's configured official Provider and positive standard USD PAYG rates. Third-party offers remain explicitly labeled.

GLM 4.5 versions

All published versions linked to this unique model. The score columns identify the version used by the current overall ranking.

1 rows
Columns

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GLM-4.5Jul 28, 202562.0355B131.1K98.3KYesMIT

What is GLM 4.5?

A concise description based on the published model registry.

GLM-4.5 is an Agentic, Reasoning, and Coding (ARC) foundation model designed for intelligent agents, featuring 355 billion total parameters with 32 billion active parameters using MoE architecture. Trained on 23T tokens through multi-stage training, it is a hybrid reasoning model that provides two modes: thinking mode for complex reasoning and tool usage, and non-thinking mode for immediate responses. The model unifies agentic, reasoning, and coding capabilities with 128K context length support. It achieves exceptional performance with a score of 63.2 across 12 industry-standard benchmarks, placing 3rd among all proprietary and open-source models. Released under MIT open-source license allowing commercial use and secondary development.

Use the benchmark, Arena and pricing sections above as separate evidence. A missing field means the current data snapshot does not support that claim.

Data snapshot: 2026-08-07. Editorial model content is not available in the backend.

GLM 4.5 vs nearby models

Open a comparison with the three ranked models immediately above and below this model.

GLM 4.5vso1GLM 4.5vsLlama 3.3 Nemotron Super 49BGLM 4.5vsLlama 3.1 Nemotron Ultra 253BGLM 4.5vso3 miniGLM 4.5vsQwen3.5 122B A10BGLM 4.5vsLongCat Flash Thinking

Models similar to GLM 4.5

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FAQ

Common questions about GLM 4.5.

When was GLM 4.5 released?

GLM 4.5's default version was released on Jul 28, 2025.

How much does GLM 4.5 cost?

No official standard PAYG price is currently available for GLM 4.5. The lowest tracked third-party offer starts at $0.286 input and $1.14 output via 302.AI.

Who created GLM 4.5?

GLM 4.5 is published under Zhipu AI in the model registry.

What is the context window for GLM 4.5?

The default version has a 131.1K token context window.

Is GLM 4.5 open weight?

Yes. The default version is marked as open weight under MIT.

How many API providers offer GLM 4.5?

4 published provider offerings are linked to the default version.

What models should I compare GLM 4.5 with?

Nearby ranked alternatives include o1, Llama 3.3 Nemotron Super 49B, Llama 3.1 Nemotron Ultra 253B.

Rankings

OverallCodingText ArenaPricing

Modalities

Image GenerationVideo GenerationSpeech-to-TextEmbeddings

Benchmarks

All BenchmarksReasoningMathCoding

Vendors

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