My first impressions on ROCm and Strix Halo
blog.marcoinacio.com
April 18, 2026
3 min read
🔥🔥🔥🔥🔥
43/100
Summary
ROCm and Strix Halo enable efficient sharing of 128GB memory between the CPU and GPU. The setup process involved using Ubuntu 24.04 LTS and required a BIOS update for PyTorch to recognize the GPU.
Key Takeaways
- ROCm and Strix Halo allow for efficient sharing of 128GB memory between CPU and GPU, requiring specific BIOS settings for optimal performance.
- A BIOS update is necessary for PyTorch to recognize the GPU, which can be done automatically via WiFi in the BIOS settings.
- Adjustments to GRUB settings are needed to optimize memory allocation for GPU usage, reserving some memory for CPU stability.
- PyTorch installation with ROCm can be complex due to dependencies, but it is achievable with specific configuration in the project setup.
Community Sentiment
Positives
- The Strix Halo's quad-channel RAM feature is significant for AI inference, as it alleviates RAM constraints that typically hinder performance.
- Performance data shared by users indicates impressive token generation speeds for the gemma4 models, showcasing the hardware's capabilities in handling large-scale AI tasks.
- The ability to update BIOS over WiFi is a modern convenience that can streamline setup processes for users, despite security concerns.
Concerns
- The article lacks detailed performance metrics and benchmarks, which are crucial for evaluating the Strix Halo's capabilities in AI applications.
- There are concerns about the security of BIOS updates via WiFi, raising questions about the safety of automatic downloads in critical system components.
- Using outdated quantization methods for LLMs can lead to suboptimal performance, indicating that the author may not be fully leveraging the hardware's potential.