The light show that runs our house at Christmas generates its own effects via a fine-tuned LLM that I trained on the same hardware that serves it. The whole stack — model training, inference, GPU audio analysis for beat detection, the dashboard — runs on a single AMD Ryzen AI MAX+ 395 (Strix Halo / Radeon 8060S / 128 GB unified memory) housed in the rack pictured. It's been my daily driver for production AI work for 6 months. Figured this sub would appreciate it.

Why AMD over NVIDIA on this build: the 128 GB unified memory pool was the killer feature. A 27B-parameter model with bf16 LoRA training plus gradient and optimizer state peaks around 80 GB — fits comfortably on this box; on the NVIDIA side it'd need an RTX 6000 Ada or a multi-GPU setup. Total cost of the Corsair AI Workstation 300 in this build was around $2,400; equivalent NVIDIA workstation is closer to $8K. The unified memory is also more flexible than separate VRAM in practice — the same pool serves training, inference, and the audio analyzer without juggling.

Day-to-day workloads on this box:

- Qwen3.5-27B fine-tuning (~12.5 min/step with Flash Linear Attention kernels, ~4-day full epoch wall-clock)

- Qwen3.6-35B-A3B MoE inference at ~50 tok/s

- GPU audio analysis for the Christmas light show in real-time (beat detection, stem separation, section segmentation)

- Code agents (Codex CLI, OpenClaw), home-assistant LLM, the usual stack

Six months in, the honest take: Strix Halo on Linux works, but it took serious work to get there. ROCm 7 nightly drivers, kernel 6.19 mainline, the whole nine yards. I've been contributing the fixes back upstream as I figure them out — the Unsloth team has merged two of my PRs so far, with two more in flight — and writing it all up so the next person doesn't have to start from zero.

Full guide is at https://github.com/h34v3nzc0dex/strix-halo-llm-finetune-guide. Happy to answer questions about the build, what does and doesn't work, or anything else.

I have a 7800X3D for my new build, but I saw this 9800X3D pop up on Amazon and I ordered it. I triple-checked that it is "sold by Amazon" and not a 3rd party seller, but it didn't ship yet and I'm starting to get nervous, because my 30 day return window for the 7800x3d is around the time this one is supposed to arrive. What are the odds this isn't legit or is canceled? Anyone have horror stories?

Just got this from Amazon, the the box seem to be already open and just taped over idk

My new build- specs are Ryzen 5 3600, RX560 xt 8gb and 8gb of 3200mhz ram (soon to be 32gb)

I’m currently developing backend software on a Ryzen 5600G and running a PHP server via Docker on Windows 11.

Compared to my other machine, a MacBook M1 Pro, it feels slightly slower overall when I am running things like a large suite of unit tests.

Will the additional boost in L3 cache on X3D based Ryzen CPUs have a major performance boost in software development? Looking at whether it’s worth the investment to upgrade to a 5700X3D as I am on an AM4 system and plan to be on it for a few years.

Thanks.

For those interested in a Ryzen Build . . . https://youtu.be/hGsOHpsnGoA

My Ryzen chip/motherboard is preordered. If you are interested to see a build vlog along with benchmark testing and gameplay footage using the new rig, I'll be sharing detailed videos along the way.

Just trying to do my part to enhance the community and bring you information if you're thinking of building a Ryzen-based system. Likes, shares, comments, and suggestions appreciated!

https://youtu.be/HpM2LMzXnlc

Hi Guys! I just got myself on to the Ryzen 395 w128gb platform (Asus ProArt Px13). I could totally use your support in answering some of the questions I have:

1. I have read that I need to recompile llama.cpp for this Ryzen machine in order to get the maximum performance out of this machine. My question is first of all is that even true? If so what do I need to do?

2. All the users of this platform, I have noticed that when I load models using lm studio (64gb GPU + 64gb system ram) I see both my system ram and GPU memory filled up. I used a memory cleaner app to free up the system ram and sure enough it freed up a lot of memory, I expected lm studio to crash but no it didn't and there model kept running, my question is why do both system memory and GPU memory fill up when I load models? Should it just the GPU memory getting filled up only?

3. I have been using lmstudio prior to this machine it still works but if I do end up recompiling an optimized version of llama.cpp will I be able to use it something like lmstudio for ease of use?

4. I have been looking into other ai server apps such as Lemonade Ai server that claim to be optimized for this platform out of the box but have found it to lackluster in terms of performance.

I understand that this might be a lot of questions but I would love to hear what your thoughts.

Hey everyone,

I’m currently running a Ryzen 9 7950X3D on an ASUS Prime X670E-Pro WiFi with 64GB of DDR5-6600 (2×32GB, dual-channel). The system runs stable – no crashes, no memory errors – even under heavy load.

Still, I keep reading that DDR5-6000 is the ideal frequency for Zen 4, especially for X3D CPUs. Some people seem to have issues above 6000, while others say it's fine if it works.

So I wanted to ask: what would you do if you were in my situation?
Would you leave the RAM at 6600 if it runs fine, or would you tune it down to something like 6400, 6200, or even 6000 just to be safe?

I’m curious to hear what others have experienced or decided in a similar setup. Appreciate any input!

Windows freezing and the screen blinking even when i doing nothing, on this video i was just moving the mouse, sometimes the LCD fans got disconfigured also. I've try everything, like removed the sound card, the fans, pull'n back the memories, format de pc, reinstall the windows, i've try windows 10, 11, and still the same. Got the latest BIOS version also. Can be BIOS BIOS config ? Any idea ? 2 Months pass by and i'm still here lol