Best AI Mini PCs for Local LLM

Bandwidth is what actually governs token speed, and the Mac Studio M4 Max has more of it than anything else in this group. At up to 546 GB/s it more than doubles the Mac mini M4 Pro's 273 GB/s and the Strix Halo boxes' 256 GB/s, and community testing puts 70B models at roughly 22-25 tokens/sec, far ahead of the rest of the field here. Macworld (4.5/5) and AppleInsider (4.5/5) both praised its performance and composure, with AppleInsider noting it is 'faster than the Apple Silicon Mac Pro, for half, and sometimes a quarter, of the price.' Its 128 GB unified memory ceiling fits 100B-class quants, and it stays cool and quiet doing it. The catch is price: roughly double the 128 GB GMKtec EVO-X2 or Beelink GTR9 Pro, and it is macOS-only, so Linux and CUDA tooling are out.

If the requirement is fitting a 120B-parameter model locally, the GMKtec EVO-X2 is the 128 GB-class mini PC to buy. PCWorld praised its 'excellent combination of CPU, GPU, and NPU performance at desktop workstation level' and scored it 4.5/5. The XDNA 2 NPU contributes 50 TOPS toward a 126 TOPS platform total once the Ryzen AI Max+ 395 and the Radeon 8060S iGPU are counted. With 128 GB of LPDDR5X at 256 GB/s it loads GPT-OSS 120B Q4 with room to spare and runs 70B-class models at 6-8 tokens/sec for a single user. Memory is soldered, and a single 2.5G Ethernet port limits clustering.

Inside, the Beelink GTR9 Pro is the same AMD Ryzen AI Max+ 395 with 128 GB LPDDR5X as the GMKtec EVO-X2: same 50 TOPS NPU, same 126 TOPS platform total, same memory ceiling. Two things separate them, dual 10GbE Intel E610 networking and an industrial-grade metal chassis. Reviewers at jasondeegan.com, starryhope, and minipcreviewer praised its workstation-class AI performance and high-bandwidth networking. Beelink shipped firmware updates in Nov 2025 and Q1 2026 that addressed NIC-related BSOD and mouse-lag issues, though Beelink support acknowledged a hardware-level issue with no complete software fix. Pick this over the EVO-X2 if you plan to cluster two boxes for distributed inference or share a 10GbE NAS at line rate. Otherwise the EVO-X2 gives you the same LLM throughput for $300 less.

The Framework Desktop puts AMD's Strix Halo silicon into an open, repairable chassis aimed squarely at local AI. PCWorld awarded it 4.5/5 and an Editors' Choice, writing that 'it's not just for tinkering, this machine can legitimately run the latest AI models locally, something few desktops this size can do.' Of its 128 GB of LPDDR5X-8000 unified memory, AMD's driver can assign up to 96 GB as VRAM, enough to run GPT-OSS 120B, which AMD says runs about ten times faster than Llama 3 70B on this chip. ServeTheHome called it 'our third-favorite AMD Strix Halo mini PC so far,' and Tom's Hardware noted 'the mix of powerful graphics and plentiful RAM is why Framework is pushing this as an AI system.' Windows and Linux both run on it, so the full open-source AI stack is available in a way it isn't on the Mac Studio. Bandwidth and price are the limits.