4 Months with Strix Halo: From Gaming to Local AI Exploration
I’ve been an AMD enthusiast since the Slot A era. My recent journey included owning the ASUS ROG Zephyrus (4800HS) and Strix Point.
As many of you know, RAM prices spiked unexpectedly earlier this year. Seeing an opportunity to grab a high-spec machine while prices were still somewhat manageable, I picked up an HP Zbook Ultra G1a with 128GB of RAM. Looking back, it seems like this specific configuration is almost impossible to find in the US now, regardless of the price.
Initially, I bought it as a step up from Strix Point, mainly hoping for more stable frame rates in certain 3D games, like Tokyo Xtreme Racer. At the time, when Lisa Su pitched this as a tool for Creators, Gamers, and AI Developers, AI wasn’t really on my radar.
That changed in April when my company started providing a subscription for a Coding AI Assistant. It made me wonder: “What can I actually do with my own laptop?”
I started experimenting with Ollama and became fascinated with abliterated LLMs. The built-in web search tools were also a huge plus. While trying to compare Vulkan and ROCm via LM Studio, I came across “Lemonade.” I realized I could run lightweight models (<10B) directly on the NPU, and now I use it as a handy, lightweight translator (since English isn’t my first language).
To be honest, Strix Halo isn’t a “perfect” AI machine, as many of you have likely experienced. It really shines with MoE models, but anything with more than 15B active parameters tends to struggle. Still, it’s enough to carve out some very practical use cases.
In terms of models, the Gemma 4 series has excellent language support. I’m currently testing gpt-oss 120b with some challenging questions to see if it truly lives up to its 120b intelligence. I’ve also found that Qwen 3.6 offers superior coding assistance compared to Gemma 4 at the same size, and Ministral serves as a great European alternative.
There are still some frustrations with AMD’s software ecosystem. For instance, EfficientNet for digiKam’s AutoTag doesn’t run on the GPU, and Lemonade lacks an auto-updater. However, I’m glad I dove into this a bit late—the practical utility has been surprisingly high.
So, that’s my experience with Strix Halo so far. How are you all getting on with your setups?