Technical Specifications

System Requirements

VRAM requirements for different quantization methods and context sizes

GLM-4-9B-Chat

The GLM-4-9B-Chat model is a conversational artificial intelligence model developed by THUDM, the Tsinghua University Department of Computer Science and Technology, in collaboration with Z.ai. It belongs to the GLM (General Language Model) series, a framework designed for broad language task performance. This model, with 4.9 billion parameters, is specifically fine-tuned for interactive dialogue and multi-turn conversational applications, excelling in the comprehension and generation of natural language.

Architecturally, GLM-4-9B-Chat is based on a dense transformer design. The underlying GLM-4 architecture incorporates key technical features such as RMSNorm for normalization and employs an autoregressive blank infilling approach during its pretraining phase. This model supports an extended context length of up to 128,000 tokens, facilitating long-range dependencies in conversational flows. The model family has enhanced its multilingual capabilities, supporting 26 languages, including Chinese, English, Japanese, Korean, and German.

GLM-4-9B-Chat is designed for a variety of general-purpose language applications. Its functional scope includes robust natural language understanding, the generation of coherent and contextually appropriate text, and proficient multilingual interaction. Beyond its core conversational abilities, the model integrates advanced functionalities such as web browsing, code execution, and the invocation of custom tools via function calls. These capabilities make it applicable for deployments in conversational AI assistants, advanced chatbots, and systems requiring automated content generation or problem-solving through external tools.

No evaluation benchmarks for GLM-4-9B-Chat available.