Apple discloses details of M1 Pro, M1 Max

October 19, 2021 // By Peter Clarke
Apple discloses details of M1 Pro, M1 Max
Apple has revealed some details of the M1 Pro and M1 Max processors have been deployed in latest MacBook Pro laptops.

The M1 Pro and M1 Max introduce a system-on-a-chip (SoC) architecture to and are manufactured in TSMC's 5nm manufacturing process and deliver up to 70 percent faster CPU performance than the original M1.

The GPU in M1 Pro is up to 2x faster than M1, while the GPU in the M1 Max is up to 4x faster than the M1

The M1 Pro offers up to 200Gbyte/s of memory bandwidth with support for up to 32Gbytes of unified memory. M1 Max delivers up to 400Gbyte/s of memory bandwidth — 2x that of M1 Pro and nearly 6x that of M1 — and support for up to 64Gbytesof unified memory.

The M1 Pro and M1 Max deliver the same performance whether the MacBook Pro is plugged in or using the battery. M1 Pro and M1 Max also feature enhanced media engines with dedicated ProRes accelerators specifically for video processing.

The M1 Pro contains 33.7 billion transistors, more than 2x the amount in M1. A 10-core CPU, including eight high-performance cores and two high-efficiency cores, is up to 70 percent faster than M1.

M1 Pro has an up-to-16-core GPU that is up to 2x faster than M1

The M1 Max features the same 10-core CPU as the M1 Pro and adds a 32-core GPU for up to 4x faster graphics performance than M1. With 57 billion transistors the M1 Max is the largest chip Apple has ever built.

The M1 Pro also includes dedicated acceleration for the ProRes professional video codec, allowing playback of multiple streams of 4K and 8K ProRes video. The M1 Max goes further, delivering up to 2x faster video encoding than M1 Pro, and features two ProRes accelerators.

Both the M1 Pro and the M1 Max include a 16-core Neural Engine for on-device machine learning acceleration and improved camera performance. Apple's custom image signal processor, along with the Neural Engine, uses computational video to enhance image quality for

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