Technical Specifications

System Requirements

VRAM requirements for different quantization methods and context sizes

ChatGLM3-6B-32K

ChatGLM3-6B-32K is an advanced large language model developed jointly by Zhipu AI and Tsinghua University's KEG Lab. This variant builds upon the foundation of ChatGLM3-6B, specifically enhancing its capabilities for processing and understanding long textual contexts. The model is engineered to effectively manage input sequences up to 32,768 tokens in length, a significant extension compared to the 8,000-token context of its predecessor.

The architectural design of ChatGLM3-6B-32K is based on the transformer framework, a common paradigm in large language models. Key innovations in this variant include updated position encoding mechanisms and a specialized training methodology tailored for long-text scenarios. This targeted approach during the conversation stage, utilizing the full 32K context length, allows the model to maintain coherence and accuracy over extended dialogues and documents.

ChatGLM3-6B-32K is designed for applications requiring deep understanding and generation of human-like text across extensive content. It natively supports various complex functionalities such as tool invocation (Function Call), code execution (Code Interpreter), and Agent tasks. This versatility makes it suitable for diverse use cases including long-form conversations, comprehensive text analysis of articles or documents, and the generation of detailed content based on provided prompts.

No evaluation benchmarks for ChatGLM3-6B-32K available.