As the title says. I run a server rack and as far as right now my strix halo sits in a T1 case but want it to move it the rack. I know they have the 10” option but can’t be used in a full size rack as far as I’m aware. So looking for any recommendations, im open to 3d printed solutions. Or even a dual system next to each other setup in case one day I can get a stack.
3xLaptops(Work, Personal,Old college giving up plex server)
2xSBC(Pi for Qbit traffic on VPN, Zima board 2 to migrate old laptop plex to)
1xPC(strix halo as local Ai server on linux and gaming)
Rack with networking equipment…
Have been fixing everything for a while… this is the cleanest the floor has been in a while…
New to r/StrixHalo 😄 So i have been running a Framework Strix Halo 128GB for the last year or so. I have used linux for the most part of my adult life, but by no means an expert at it. My background is in devices, and processing, and even trained models while in college, came with the plan of learning how to deploy and implement a local solution.
LM studio and Hermes/ClaudeCode running locally to automate some task. I use tailscale to access it from a terminal in my phone, or the discord gateway.
Have been using Qwen3.6 35B A3B Q8 mainly.
Have been trying to test a couple of different parameters on the agents or LM Studio, vulkan(rocm always fails to load for some reason), to try to optimize the processing time of some task since it feels like it can take forever to complete certain task. I have looked into optimizing prompt task breakdown to improve in terms of the context, but still feel it leaves a lot to be desired in terms of latency.
Is there a good way our resources to look at impact that parameters like eval_batch_size, physical_batch_size, etc, have on the performance of agentic workflows? Have been messing with many of them but truthfully I don't have a good metric other than "vibes". You can tell me tokens/s but while testing it on actual work flows like, go look for this file and tell me xyx, hell.... just prompt it with "test" and waiting 30secs for it to get back to me feels like I'm doing something wrong. Is literally a tool i give it a task, and comeback in 15 min, and 80% it works, and 20% needed more context. I use claude code at work and if I could get 1/10 the performance I have there i would be satisfied, to be fair the task I want to work at home are not remotely as complex as what i ask for at the office.
Any advice? From trying different models, different Q, different batch sizes, context length, or a good solution for benchmark optimal parameters.