The new M6 MacBook Pro limits unified memory to 32GB, forcing users needing 64GB or more to choose last-gen M5 Pro/Max models, which also offer Thunderbolt 5 and more external displays; the article compares specs, pricing, and provides decision guidelines for running local LLMs of different sizes.
Apple released two MacBook Pro models in one week: the M6 starting at ¥15,999 with the latest chip but no touchscreen, and the Touchscreen PROLED at ¥22,999 with an OLED touchscreen but last-gen M5 Pro/Max chips. The article compares specs, trade-offs, and gives buying advice based on budget and needs.
This article analyzes Mac mini M6 and M5 Pro hardware for local LLM deployment, detailing memory constraints (32GB vs 64GB unified memory), bandwidth limits (170GB/s vs 307GB/s), model sizing using the 0.7 memory rule, recommended software stacks (Ollama, MLX, llama.cpp), three deployment tiers for 14B, 70B, and 100B+ models, and five practical pitfalls to avoid.
Inco AI's open-source inference engine Splash 1.4.0 achieves 120 tokens/second decode and 1.3K tokens/second prefill on a 64GB M5 Pro running Qwen3.8-Flash-Next, outperforming Ollama by 3x and Strata by 30%, with MoE activation efficiency enabling large models on modest memory.
