Zhipu AI Open-Sources GLM-4.1V-Thinking: A Leap in Multimodal Reasoning

Zhipu AI has unveiled its latest general vision model, GLM-4.1V-Thinking, now available as an open-source project. Built on the GLM-4V architecture, this model introduces a chain-of-thought reasoning mechanism, significantly boosting its ability to tackle complex cognitive tasks.

Enhanced Multimodal Capabilities

The model supports multimodal input, including:

• Images
• Videos
• Documents

It excels in diverse scenarios such as:

• Long video understanding
• Image question answering
• Subject problem-solving
• Text recognition
• Document interpretation
• GUI Agent operations
• Code generation

These capabilities make it suitable for applications across education, research, and business.

Performance Benchmarks

GLM-4.1V-Thinking has demonstrated outstanding performance in 28 authoritative evaluations. Key highlights include:

• Achieved top results among 10B-level models in 23 benchmarks.
• Matched or surpassed the 72B parameter Qwen-2.5-VL in 18 benchmarks.
• Excelled in tests like MMStar, MMMU-Pro, ChartQAPro, and OSWorld.

The model's 9 billion parameters and efficient inference allow it to run on a single NVIDIA 3090 GPU, making it accessible to developers under a free commercial license.

Technical Innovations

Zhipu AI has enhanced the model's cross-domain reasoning through:

• Reinforcement learning techniques
• Curriculum sampling methods These improvements enable the model to demonstrate deep thinking and problem-solving abilities for complex issues.

The model is now available on HuggingFace, allowing global developers to experience its capabilities for free.

Industry Impact

The release of GLM-4.1V-Thinking is expected to accelerate the adoption of multimodal AI in various sectors. Experts view this as a significant step toward general artificial intelligence, further solidifying Zhipu AI's position as a leader in the field.

Key Points:

1. Open-source release of GLM-4.1V-Thinking with enhanced reasoning capabilities.
2. Supports multimodal inputs (images, videos, documents) for diverse applications.
3. Outperforms larger models in multiple benchmarks while being resource-efficient.
4. Available for free commercial use on HuggingFace.