LLM Mini PC War Is On: Beelink Enters the Race with $1,800 Strix Halo-Powered GTR9 Pro AI
The landscape for compact, high-memory systems capable of local Large Language Model (LLM) inference is steadily expanding, with Beelink now officially announcing its GTR9 Pro AI Mini. This unit joins a growing roster of Mini-PCs built around AMD’s Ryzen AI MAX+ 395 “Strix Halo” APU, a platform that has garnered considerable attention since its initial reveal five months ago, particularly for its potential in on-premise AI.
Specs and Features
The Beelink GTR9 Pro AI Mini is specified to feature the AMD Ryzen AI MAX+ 395 processor, incorporating the Radeon 8060S integrated graphics with its 40 RDNA 3.5 Compute Units. Crucially for LLM workloads, the system will support up to 128GB of LPDDR5X system memory. Users will reportedly be able to allocate a substantial portion of this unified memory as VRAM – up to 96GB on Windows or a more generous 110GB on Linux. This VRAM capacity directly addresses a primary bottleneck for running larger quantized models, such as 70B parameter variants (e.g., Llama-3-70B-Instruct-IQ4_XS), locally. Connectivity is also a notable point, with the GTR9 Pro AI Mini set to include dual 10Gbps Ethernet ports and dual USB4 ports, offering robust I/O for demanding users.
Competing Strix Halo Mini-PCs
This announcement follows a recent trend of Strix Halo-based Mini-PCs. As we’ve previously discussed, systems like the FAVM FX-EX9 and the GMKtec EVO-X2 are also targeting this niche. The FAVM unit, for instance, similarly promises 128GB of memory with up to 110GB allocatable as VRAM, and interestingly includes an OCuLink port for potential external GPU expansion. The GMKtec EVO-X2, officially priced around $2,000, also boasts a 128GB memory configuration. Beelink is reportedly targeting a price around $1,800 USD for the GTR9 Pro AI Mini.
Performance Considerations for LLM Workloads
For the technically-inclined LLM enthusiast, the key metric beyond VRAM capacity is memory bandwidth. Strix Halo APUs feature a 256-bit LPDDR5X memory interface, translating to approximately 256 GB/s of bandwidth. While a significant figure for an integrated solution, and certainly enabling for models up to 70B_q4, it’s important to contextualize this. For instance, a discrete NVIDIA RTX 3060 12GB offers 360GB/s, and higher-tier cards substantially more. This difference will manifest in token generation speeds, particularly for larger models. Based on similar Strix Halo configurations, one might anticipate performance for 4-bit quantized 70B models in the range of 5-9 tokens/second, which is functional but modest compared to dedicated multi-GPU setups. Prompt processing speeds will also be influenced by this bandwidth.
Availability
The availability of Ryzen AI MAX+ 395 systems is gradually improving. While the ASUS ROG Flow Z13 with 128GB RAM has faced stocking challenges, its 64GB variant sees more consistent availability. The GMKtec EVO-X2 is currently orderable through Amazon (#ad) and its official site, though tariffs may apply for direct purchases.
From a value perspective, an ~$1800 price for the Beelink GTR9 Pro AI Mini warrants careful consideration. The substantial, configurable VRAM from its 128GB pool in a compact form factor is appealing. The dual 10G Ethernet ports are a distinct advantage for users with high-speed network storage or specific distributed computing interests. However, enthusiasts focused purely on maximizing tokens-per-dollar for large models might still find better raw performance by assembling systems with multiple second-hand discrete GPUs, albeit with trade-offs in size, power consumption, and system complexity.
Final Thoughts
The Beelink GTR9 Pro AI Mini, with its specific VRAM allocation capabilities and strong connectivity, presents another interesting option in the evolving market for local LLM hardware. Its success will depend on final pricing, availability, and how effectively its performance-per-dollar stacks up against both other Strix Halo offerings and alternative custom-built solutions.
