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ZGLM 4.5OPEN

GLM-4.5 is our latest flagship foundation model, purpose-built for agent-based applications.

131KContext window · tokens
$0.6Input price · per M tokens
$2.2Output price · per M tokens
Z.AIProvider

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Benchmarks & performance

Independent benchmark scores for GLM 4.5, measured by Artificial Analysis. Higher is better. Measurement mode: Reasoning.

Intelligence index19.7
Math index73.7
GPQA78.2%
MMLU-Pro83.5%
Humanity's Last Exam13%
Long Context Reasoning51.7%
LiveCodeBench73.8%
SciCode34.8%
MATH-50097.9%
AIME87.3%
AIME 202573.7%
IFBench44.1%
τ²-Bench43%
Terminal-Bench Hard22%
vs. models measured heretop 65%
Scores higher than 35% of the 273 models measured by Artificial Analysis and tracked here.
Models at this level cost $0.88 per 1M tokens (median of 23) — this one costs $1.
Cheaper and better on this index: GLM 5.3 Flash · Gemini 3.7 Flash · Gemini 3.7 Flash (batch) and 68 more
Benchmark data by Artificial Analysis

About this model

GLM 4.5 is an open-weight AI model by Z.AI. You can download and self-host it for free; the prices below are hosted-API list prices, tracked daily, for when you prefer convenience over self-hosting.

Frequently asked questions

What is GLM 4.5?

GLM 4.5 is an AI language model from Z.AI. It is open-weight: you can download it and run it on your own hardware, for free. It scores 19.7 on the Artificial Analysis intelligence index.

Is GLM 4.5 free?

The weights are free and open — you can self-host GLM 4.5 and pay nothing per token. If you prefer a hosted API, list prices are $0.6 per million input tokens and $2.2 per million output tokens.

What is GLM 4.5 good at?

Independent benchmarks from Artificial Analysis give it GPQA 78.2%, MMLU-Pro 83.5%, Humanity's Last Exam 13%, Long Context Reasoning 51.7%, LiveCodeBench 73.8%, SciCode 34.8%, MATH-500 97.9%, AIME 87.3%, AIME 2025 73.7%, IFBench 44.1%, τ²-Bench 43%, Terminal-Bench Hard 22%. It is particularly used for mathematical reasoning.

Can I self-host GLM 4.5?

Yes. GLM 4.5 has open weights, so you can download it and run it on your own GPU or server with tools like Ollama, vLLM or llama.cpp — with no per-token cost.

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