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ZGLM 4.5VOPEN

GLM-4.5V is a vision-language foundation model for multimodal agent applications.

66KContext window · tokens
$0.6Input price · per M tokens
$1.8Output price · per M tokens
Z.AIProvider

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Benchmarks & performance

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

Intelligence index9
Math index73
GPQA68.4%
MMLU-Pro78.8%
Humanity's Last Exam6.3%
Long Context Reasoning0%
LiveCodeBench60.4%
SciCode22.1%
AIME 202573%
IFBench34.2%
τ²-Bench22.5%
Terminal-Bench Hard5.3%
💰 Blended price$0.9 / 1M tokens
📈 Value10 intelligence points per $
vs. models measured heretop 87%
Scores higher than 13% of the 273 models measured by Artificial Analysis and tracked here.
Models at this level cost $0.22 per 1M tokens (median of 28) — this one costs $0.9.
Cheaper and better on this index: GLM 5.3 Flash · Gemini 3.7 Flash · Gemini 3.7 Flash (batch) and 103 more
Benchmark data by Artificial Analysis

About this model

GLM 4.5V 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 4.5V?

GLM 4.5V 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 9 on the Artificial Analysis intelligence index.

Is GLM 4.5V free?

The weights are free and open — you can self-host GLM 4.5V and pay nothing per token. If you prefer a hosted API, list prices are $0.6 per million input tokens and $1.8 per million output tokens.

What is GLM 4.5V good at?

Independent benchmarks from Artificial Analysis give it GPQA 68.4%, MMLU-Pro 78.8%, Humanity's Last Exam 6.3%, Long Context Reasoning 0%, LiveCodeBench 60.4%, SciCode 22.1%, AIME 2025 73%, IFBench 34.2%, τ²-Bench 22.5%, Terminal-Bench Hard 5.3%. It is particularly used for mathematical reasoning.

Can I self-host GLM 4.5V?

Yes. GLM 4.5V 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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