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LatestZhipu AI4.1V
Zhipu AIVision-Language

Zhipu AI Open-Sources 9B Vision Model with 'Thinking' Mode

The new GLM-4.1V-9B-Thinking model makes its vision and chain-of-thought reasoning capabilities available under a permissive MIT license.

Jun 28, 2025
NotableMIT
GLM-4.1V-9B-Thinking

Zhipu AI has released a new open-source vision-language model, GLM-4.1V-9B-Thinking. At 9 billion parameters, the model is designed to interpret and reason about visual inputs, marking another significant entry into the competitive field of multimodal AI.

The model's most distinct feature is its explicit "thinking" mode. This enables a chain-of-thought process, where the model generates intermediate reasoning steps before arriving at a final answer. For developers and researchers, this transparency can make it easier to understand and debug the model's conclusions on complex visual question-answering tasks.

Permissive Licensing for Broader Use

Perhaps most notably for the open-source community, Zhipu AI has released the model under the highly permissive MIT license. This choice removes significant barriers to adoption, allowing for broad use in both commercial applications and academic research. The move encourages wider experimentation and integration compared to models with more restrictive licenses.

The complete model weights and details are available for download on Hugging Face. This release provides developers with a powerful and transparent tool for building applications that require a sophisticated understanding of both language and imagery.

Sources

  • zai-org/GLM-4.1V-9B-Thinking

    Hugging Face

    Visit
OlderOvis-U1-3B Unifies Image Understanding and GenerationAIDC-AI · Any-to-Any · last yearNewerKyutai Releases 1.6B Bilingual TTS ModelKyutai · Text → Speech · last year

Get the model

Hugging Face

Specs

Parameters9B
Context window66K tokens
Size20.6 GB
PrecisionBF16
ArchitectureGlm4vForConditionalGeneration
LicenseMIT
Downloads60.4K
Likes793

Can you run it?

Runs on a laptop — about 7.5 GB at 4-bit.

  • BF16 (as published)

    24 GB GPU (RTX 3090 / 4090) · 32 GB Mac

    21.9 GB
  • 8-bit

    16 GB GPU (RTX 4080 / 5070 Ti) · 24 GB Mac

    12.3 GB
  • 4-bit

    8 GB GPU (RTX 4060) · 16 GB laptop or Mac

    7.5 GB
Your machine
GGUF builds
  • KV cache sized for 8,192 tokens of context; longer prompts need proportionally more.

Based on Hugging Face weights metadata. Assumes an 8K context and ~1 GB runtime overhead; actual needs vary. How we estimate


Modalities

ReasoningVision-Language

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