Running GLM-5.2 Locally: Expert Consensus

• GLM-5.2 can be run on local hardware with significant performance
• Required hardware includes high-end GPUs and substantial RAM
• Expert opinions vary on the cost and feasibility of local implementation

The Buzz Score

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

Forum Voices

Experts weigh in on the feasibility of running GLM-5.2 locally.

I run Q4_K_XL. All it takes to run to get about 6tk/sec is 512gb of ram and 2 3090 GPUs with llama.cpp -cmoe.

GLM 5.2 is the first time I’m actually excited about AI! I’m not the most bullish on AI code for several few reasons, but the biggest reason is the ownership model.

Technical Requirements

Running GLM-5.2 locally requires significant hardware investments, including high-end GPUs and substantial RAM.

it can fit on 256GB of RAM, but it will be heavily quantized and still run very slowly.

Focus Keyword: GLM 5.2