GLM-4-9B
| Property | Value |
|---|---|
| Parameter Count | 9.4B |
| Tensor Type | BF16 |
| License | GLM-4 |
| Paper | ArXiv |
| Context Length | 8K tokens |
What is GLM-4-9B?
GLM-4-9B is a state-of-the-art language model developed by THUDM that represents the latest generation in the GLM-4 series. This base model demonstrates exceptional performance across multiple domains, consistently outperforming comparable models like Llama-3-8B in crucial benchmarks including MMLU (74.7%), C-Eval (77.1%), and GSM8K (84.0%).
Implementation Details
The model is implemented using the Transformers architecture and utilizes BF16 tensor precision for optimal performance. It supports a context window of 8K tokens and serves as the foundation for various specialized versions, including chat models and long-context variants.
- Multilingual support for 26 languages including English, Chinese, Japanese, Korean, and German
- Advanced semantic understanding and reasoning capabilities
- Optimized for both research and production environments
Core Capabilities
- Superior performance in mathematical reasoning (GSM8K: 84.0%)
- Strong code generation abilities (HumanEval: 70.1%)
- Excellent multilingual comprehension and generation
- Robust knowledge assessment performance (MMLU: 74.7%)
Frequently Asked Questions
Q: What makes this model unique?
GLM-4-9B stands out for its exceptional performance-to-size ratio, offering superior capabilities across multiple benchmarks while maintaining a relatively compact 9.4B parameter count. It serves as a versatile base model that can be fine-tuned for various specialized applications.
Q: What are the recommended use cases?
The model is particularly well-suited for tasks requiring strong reasoning capabilities, mathematical problem-solving, code generation, and multilingual applications. It can serve as a foundation for building specialized chat models, long-context variants, and multi-modal applications.
