CogVLM
by Tsinghua University
Powerful vision-language model with strong visual grounding.
Quick Facts
- Model Size
- 17B
- Context Length
- 2K tokens
- Release Date
- Oct 2023
- License
- Apache 2.0
- Provider
- Tsinghua University
- KYI Score
- 8.3/10
Best For
Performance Metrics
Speed
Quality
Cost Efficiency
Specifications
- Parameters
- 17B
- Context Length
- 2K tokens
- License
- Apache 2.0
- Pricing
- free
- Release Date
- October 25, 2023
- Category
- multimodal
Key Features
Pros & Cons
Pros
- ✓Strong visual grounding
- ✓Apache 2.0
- ✓Good performance
Cons
- !Less known
- !Shorter context
- !Resource intensive
Ideal Use Cases
Visual analysis
Document understanding
Image Q&A
OCR
CogVLM FAQ
What is CogVLM best used for?
CogVLM excels at Visual analysis, Document understanding, Image Q&A. Strong visual grounding, making it ideal for production applications requiring multimodal capabilities.
How does CogVLM compare to other models?
CogVLM has a KYI score of 8.3/10, with 17B parameters. It offers strong visual grounding and apache 2.0. Check our comparison pages for detailed benchmarks.
What are the system requirements for CogVLM?
CogVLM with 17B requires appropriate GPU memory. Smaller quantized versions can run on consumer hardware, while full precision models need enterprise GPUs. Context length is 2K tokens.
Is CogVLM free to use?
Yes, CogVLM is free and licensed under Apache 2.0. You can deploy it on your own infrastructure without usage fees or API costs, giving you full control over your AI deployment.