GLM-4.5V

About

What GLM-4.5V is

GLM-4.5V This model is part of the GLM-V family of models, introduced in the paper GLM-4.1V-Thinking and GLM-4.5V: Towards Versatile Multimodal Reasoning with Scalable Reinforcement Learning. - Paper: https://huggingface.co/papers/2507.01006 - GitHub Repository: https://github.com/zai-org/GLM-V/ - Online Demo: https://chat.z.ai/ - API Access: ZhipuAI Open Platform - Desktop Assistant App: https://huggingface.co/spaces/zai-org/GLM-4.5V-Demo-App - Discord Community: https://discord.com/invite/8cnQKdAprg Introduction & Model Overview Vision-language models (VLMs) have become a key cornerstone of intelligent systems. As real-world AI tasks grow increasingly complex, VLMs urgently need to enhance reasoning capabilities beyond basic multimodal perception — improving accuracy, comprehensiveness, and intelligence — to enable complex problem solving, long-context understanding, and multimodal agents. Through our open-source work, we aim to explore the technological frontier together with the community while empowering more developers to create exciting and innovative applications. This Hugging Face repository hosts the GLM-4.5V model, part of the GLM-V series. GLM-4.5V GLM-4.5V is based on ZhipuAI’s next-generation flagship text foundation model GLM-4.5-Air (106B parameters, 12B active). It continues the technical approach of GLM-4.1V-Thinking, achieving SOTA performance among models of the same scale on 42 public vision-language benchmarks. It covers common tasks such as image, video, and document understanding, as well as GUI agent operations. Beyond benchmark performance, GLM-4.5V focuses on real-world usability. Through efficient hybrid training, it can handle diverse types of visual content, enabling full-spectrum vision reasoning, including: - Image reasoning (scene understanding, complex multi-image analysis, spatial recognition) - Video understanding (long video segmentation and event recognition) - GUI tasks (screen reading, icon recognition, desktop operation assistance) - Complex chart & long document parsing (research report analysis, information extraction) - Grounding (precise visual element localization) The model also introduces a Thinking Mode switch, al

Summarised from the published model card. Read the full card on the HuggingFace links below.

Specifications

What it is

How it works

How language models work

Variants

Sizes & precisions

Open weights ship in several sizes and precisions. One page, all the variants — pick the one that fits your GPU. VRAM figures are estimates from model size.

Using it via the API

Call it like any OpenAI endpoint

Once AxForge deploys glm-4-5v for you, it answers on the OpenAI-compatible API — the same base URL and keys as every other model. (glm-4-5v below is illustrative; you get the exact model name on deployment.)

$ curl -sS https://api.axforge.ai/v1/chat/completions \
  -H "Authorization: Bearer $AXFORGE_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"model":"glm-4-5v","messages":[{"role":"user","content":"Hello"}]}'

Details

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Papers

Licence

Open weights

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