A Reddit user named Intrepid_Rub_3566 has shared a video review evaluating the performance of GLM 5.2 running on a dual AMD Strix Halo setup with 256GB of RAM. The discussion centers on whether this specific hardware configuration provides sufficient value for local large language model inference. The content highlights the technical feasibility of deploying GLM 5.2 in such an environment, focusing on resource utilization and speed. Viewers are directed to a YouTube link for detailed benchmarks and performance metrics. The thread also includes community comments discussing the practicality and cost-effectiveness of this dual-GPU approach.
media
r/LocalLLaMA
·
90d ago
·
open_models
GLM 5.2 on Dual Strix Halo (256GB): Worth it?
from English
Related articles
media
r/LocalLLaMA
·
81d ago
·
13 views
GLM5.2 performance
A Reddit user is collecting inference speed data for Nvidia’s 460GB nvfp4 checkpoint of GLM5.2 from the community.
media
r/LocalLLaMA
·
82d ago
·
6 views
GLM5.2 on 5x Pro 6000s and a 5090, an expensive journey
A user details their extensive hardware upgrade process to run the GLM 5.2 model locally, culminating in a setup of five AMD Radeon Pro W6800 GPUs and one NVIDIA RTX 5090.
github
llama.cpp
·
3d ago
·
21 views
llama.cpp b11059 adds F16 support to the Metal FWHT kernel
The llama.cpp project released build b11059, which introduces significant updates to the Metal backend for Apple Silicon hardware. The primary change is the addition of F16 input support to the Fast Walsh-Hadamard Transform (FWHT) kernel, allowing it to read F16 sources directly without requiring a converted copy.
github
llama.cpp
·
5d ago
·
22 views
llama.cpp raises Vulkan mul_mat_id expert limit to 1024
The llama.cpp project has increased the hoisted row-id limit for the Vulkan mul_mat_id operation from 256 to 1024 experts. This change addresses performance bottlenecks in models with large expert counts, such as Qwen3.8-Flash-Next, which previously ran on a slower code path due to shared array size constraints.
media
r/LocalLLaMA
·
6d ago
·
13 views
GLM details its inference infrastructure in a new blog post
The GLM team has published a blog post on z.ai detailing the architecture and design of their inference infrastructure.