Executive TL;DR

• GLM-5.2 requires 24GB of VRAM and 256GB of RAM for MoE offloading.
• Running GLM-5.2 on local hardware is possible but needs high-end GPUs.
• Quantization analysis shows a 2.5% loss in token agreement.

The Internet’s Verdict: 70% Hyped, 30% Skeptical

Introduction to GLM-5.2

GLM-5.2 is a powerful model that can be run on local hardware. However, it requires significant resources.

Hardware Requirements

A machine with 192GB RAM and an RTX 3090 24GB can almost run GLM-5.2.

My machine with 192GB RAM + RTX 3090 24GB can almost run this. It says it needs 24GB of VRAM and 256GB of RAM for MoE offloading.

Quantization Analysis

Quantization analysis shows a 2.5% loss in token agreement.

It says ‘dynamic 4-bit UD-Q4_K_XL and dynamic 5-bit UD-Q5_K_XL are generally lossless’ while showing a top-1% token agreement on the chart of 97.5%. Not what I would consider ‘generally lossless’.

Conclusion

Running GLM-5.2 on local hardware is possible but requires significant resources and may result in a 2.5% loss in token agreement.

Focus Keyword: GLM-5.2