For users whose workloads include on-device AI inference, complex 3D rendering, or other GPU-bound or memory-intensive tasks, the jump from M4 to M5 is material. The combination of per-core Neural Accelerators, higher memory bandwidth, and new GPU architecture produces multi-fold speed-ups in certain AI operations. In environments where time-to-result directly affects workflow, such as local LLMs, diffusion models, video enhancement, or ray-traced production or gaming, the M5 represents a meaningful step-change rather than a minor iteration.
By contrast, for typical day-to-day usage, browsing, office work, media playback, basic editing, and general responsiveness, the difference is unlikely to be perceptible. The M4 was already a high-performance chip that routinely exceeded the demands of normal Mac and
iPad workloads, leaving little visible headroom to exploit with the M5. In non-specialist scenarios, devices equipped with the M4 remain effectively indistinguishable in experience from those running with an M5.