A Microsoft MVP based in Japan benchmarked seven local large language models on an NVIDIA DGX Spark, running identical Japanese business questions to compare speed, format adherence, and answer qualit…
A new llama.cpp patch called HotPin enables running a 120-billion-parameter mixture-of-experts (MoE) model on just 24GB of RAM, achieving up to 67% memory savings and a 45% speedup over standard swapp…
Zhipu AI's GLM model family spans a 6,000x range in hardware requirements, with the flagship model needing more memory than a typical home has RAM, according to a user who tested GLM-4.7-Flash on a 16…
Researchers at Eternis trained probes on internal representations of large language models to achieve better calibration than chain-of-thought reasoning. The probes detected when models concealed evid…
GLM, the model family from Z.ai (formerly Zhipu AI), is gaining attention for its open weights and strong benchmark numbers. A developer tested GLM-4.7-Flash, a 30B-A3B MoE model, on a single-GPU home…
A team of engineers successfully ran the 754-billion parameter GLM-5.1 large language model on a consumer PC with only 16GB of RAM and a Ryzen 5 5600G CPU, achieving zero crashes or out-of-memory erro…