Apple’s new OLED MacBook Pros, featuring M5 Pro and M5 Max chips with up to 128GB RAM, offer enhanced AI performance through faster memory bandwidth and improved GPU cores, making them well-suited for running large local AI models. While pricier than previous models and comparable NVIDIA laptops, these MacBooks provide a premium display, portability, and strong AI capabilities, especially for users prioritizing macOS and local AI workloads.
Apple recently announced new MacBook Pros featuring OLED displays with touch functionality, available in 14- and 16-inch models. These laptops come with the M5 Pro and M5 Max chips, offering up to 128GB of memory and improved cooling in a lighter design. Prices start at $2,899, which is $400 more than the previous generation, with storage options now reaching up to 16TB. The OLED screen and Dynamic Island replace the older notch design, enhancing the user experience, but the core chip architecture remains largely the same as before.
When it comes to running local AI models, the key factors are the laptop’s reading and writing speeds. Reading involves processing the entire input prompt simultaneously, which benefits from more graphics cores, while writing outputs tokens sequentially and depends heavily on memory bandwidth. The M5 Max chip, especially the 40-core GPU version, excels here with up to 614 GB/s memory bandwidth, significantly faster than base M5 or M6 chips. This translates to faster AI model performance, with the M5 Max writing about 25 tokens per second and reading large documents much quicker than previous generations.
Memory size is crucial for running larger AI models locally because the entire model must fit into RAM. For example, a 27-billion parameter model like Qwen 3.8 requires substantial memory to maintain a useful context window. With 16GB RAM, only small models fit comfortably, while 32GB allows limited context windows for larger models. At 64GB and above, users can run bigger models with longer context windows, and 128GB enables running very large models with extensive context, such as 100-billion parameter models. Apple’s memory upgrades have become more expensive, reflecting broader market trends, which impacts the overall cost of AI-capable machines.
Comparing Apple’s new MacBook Pros to NVIDIA-powered Windows laptops reveals that Apple’s M5 Max offers about 1.5 times faster writing speeds and comparable reading speeds. However, NVIDIA laptops tend to be cheaper, with similar memory configurations costing around $800 less. Many users choose NVIDIA for Windows compatibility or specific software needs, but for those prioritizing local AI speed and macOS, the MacBook Pro remains a strong contender. The new OLED screen and lighter design add value but come at a premium price.
In conclusion, the new MacBook Pro with OLED is a solid choice for local AI workloads, especially if you value the improved display and portability. The M5 Max chip delivers excellent AI performance, particularly with the 40-core GPU and higher memory configurations. Whether to upgrade depends on your budget and needs; the previous generation still offers strong performance at a lower price. For serious AI users, investing in 64GB or 128GB of RAM is recommended to handle larger models and longer context windows effectively.