GEEKOM AI A7 MAX Mini PC (Ryzen 9 7940HS, 16GB DDR5) vs GMKtec M6 Ultra Mini PC (Ryzen 7 7640HS, 32GB DDR5)

GMKtec M6 Ultra Mini PC (Ryzen 7 7640HS, 32GB DDR5) edges ahead with 32 GB vs 16 GB — enough headroom to run larger quantized models without offloading. GMKtec M6 Ultra Mini PC (Ryzen 7 7640HS, 32GB DDR5)'s 68 GB/s bandwidth also generates tokens faster.

Neither is optimised for image generation, but GMKtec M6 Ultra Mini PC (Ryzen 7 7640HS, 32GB DDR5)'s 68 GB/s bandwidth makes generation faster. Both run SDXL via Metal (macOS) or ROCm (Linux). Expect slower generation times than a discrete GPU.

Both draw around 45W at peak load.

Both products are closely matched. Your choice should come down to price, ecosystem preference, and the specific models you plan to run.

Q1Which runs Ollama faster — GEEKOM AI A7 MAX Mini PC (Ryzen 9 7940HS, 16GB DDR5) or GMKtec M6 Ultra Mini PC (Ryzen 7 7640HS, 32GB DDR5)?

GEEKOM AI A7 MAX Mini PC (Ryzen 9 7940HS, 16GB DDR5) runs Ollama faster. Its 68 GB/s memory bandwidth vs 68 GB/s means faster token generation — roughly 1.0× more tokens/second on the same model. On Llama 3.1 8B, expect around 2 tok/s vs 2 tok/s.

Q2Can either mini PC run Llama 3 70B?

Neither mini PC has enough memory for Llama 3 70B without heavy CPU offloading (39 GB required at Q4_K_M). You would need a Mac Mini M4 Pro with 64 GB unified memory or a discrete GPU with 24 GB VRAM paired with ample system RAM.

Q3Which is better value for local AI in 2026?

GEEKOM AI A7 MAX Mini PC (Ryzen 9 7940HS, 16GB DDR5) offers better performance-per-dollar for AI workloads due to its 68 GB/s bandwidth advantage. However, if price is the primary concern and 7B–13B inference is the goal, both get the job done — the gap matters more at higher workloads and model sizes.

Q4Which has better software support for local AI?

Both run Ollama well. AMD-based mini PCs offer ROCm acceleration on Linux; Intel-based ones are adding OpenVINO support. macOS Apple Silicon has the most polished Ollama experience.