Project AURIONAI Use-Cases Research & Innovation
Z.ai (Zhipu)
multimodal LLM

GLM-4.5V

Z.ai vision-language foundation model for multimodal agent applications covering image, video, document and GUI tasks.

GLM-4.5V radar chart against baselines and bar chart of reinforcement learning gains.
Levelmodel
Classmultimodal LLM
Parameters106B
Context65,536
Released11 Aug 2025
Opennessopen weights permissive
Runs onnot in the notes
Statusactive

Lineage

finetune
GLM-4.5-Air-Base to GLM-4.5V: finetune, high confidenceGLM-4.5-Air-BaseGLM-4.5-Air-BaseZ.ai (Zhipu)GLM-4.5VGLM-4.5VZ.ai (Zhipu), Aug 2025
Z.ai (Zhipu)GLM-4.5-Air-Base is the parent (finetune)high confidenceHugging Face base_model
Where this comes from
Parent and child relations from model cards, Hugging Face base_model fields and the genealogy tables of the research notes. The tree shows two generations each way, 2 models. Confidence and evidence are the notes' own.

R&D Topics

Runtimes

Identity

Developer
Z.ai (Zhipu)
Family
GLM
Released
11 Aug 2025 sourcesannouncement page
Weights published
10 Aug 2025
Record checked
11 Oct 2026
Where this comes from
Developer and dates from the research notes. Release date is the vendor's public announcement; weights date is when open weights were published.

Architecture and Size

Architecture
MoE Built on the GLM-4.5-Air text foundation model; thinking mode switch
Total parameters
106B sources
Active parameters
12B
Checkpoint parameters
–
Context length
65,536 tokens
Input
text, image, video
Output
text
Where this comes from
Parameter counts as the developer states them. Where the checkpoint holds a different total, both are shown (register A16).

Openness and Access

Openness
open weights permissive
Licence
MIT License sources
Access routes
API, open weights download
Where this comes from
The licence file governs over registry tags and aggregator labels.

Deployment

Runs on
not in the notes
Footprint
16K max output tokens on the Z.ai API
Runtimes
SGLang
Where this comes from
Deployment tiers and runtimes as named in the notes. Footprint is the notes' figure, not a measurement by AURION.

Indonesia

Indonesian support
not stated
Regional languages
not in the notes
Jakarta hosting
unknown
Languages
Hugging Face language tags: zh, en
Where this comes from
Indonesia fields are carried on every model; unknown is an allowed value.

Benchmark Results

The notes record no benchmark result for this model.

Industry Use Cases

No industry use case links this model.

Sources

  1. huggingface.co/zai-org/GLM-4.5V https://huggingface.co/zai-org/GLM-4.5V
  2. docs.z.ai/guides/vlm/glm-4.5v https://docs.z.ai/guides/vlm/glm-4.5v
  3. openrouter.ai/z-ai/glm-4.5v https://openrouter.ai/z-ai/glm-4.5v

To cite this page: Project AURION, AI Use-Cases Research & Innovation, "GLM-4.5V", https://aurion.semai.id/models/zhipu-zai-glm-4-5v/, records of October 2026.