Applications

Where AI is actually being used: products, industries, and the work it changes.

  • Snapdragon 8 Gen 2

    First Snapdragon with INT4 support. The precision floor dropped, which is what later enabled on-device LLM work.

  • Snapdragon 8 Gen 3

    Qualcomm’s peak disclosure: an explicit parameter ceiling and token rate against a named model. Neither successor repeated it.

  • Snapdragon 8 Gen 1

    A wider tensor accelerator for camera and voice AI, with no transformer or generative capability in view.

  • Apple A19 Pro

    The first A-series where Apple’s headline AI number describes the GPU rather than the Neural Engine.

  • Apple A20 Pro

    Apple’s first 2nm phone chip and its first dual-NPU design, with 50 per cent more memory bandwidth, which matters more for model…

  • Apple A18 Pro

    The genuine change was memory bandwidth, which Apple tied directly to Apple Intelligence latency rather than to Neural Engine throughput.

  • Apple A19

    The architectural shift: AI matrix acceleration moves into every GPU core rather than the NPU carrying generative work alone.

  • Apple A18

    The Neural Engine was explicitly re-tuned for large generative models, but Apple benchmarked it against the A16, not the A17 Pro.

  • Apple A16 Bionic

    A marginal Neural Engine step. The real A16 story was imaging and display, not AI.

  • Apple A17 Pro

    The industry’s first 3nm phone chip, and the first A-series for which Apple published no operations-per-second figure at all.