As I was hoping. From https://en.wikipedia.org/wiki/Apple_A16
The Apple A16 Bionic features an Apple-designed 64-bit six-core CPU implementing ARMv9  with two “Everest”  high-performance cores running @3,46GHz and four “Sawtooth”  energy-efficient cores running @2,02GHz, in a similar design to the A15 processor on iPhone 13.
And footnote  is from https://www.cpu-monkey.com/en/cpu-apple_a16_bionic
Instruction set (ISA): ARMv9-A64 (64 bit)
Though how “cpu monkey” knows for sure I really don’t know.
Anyway, glad to see that (apparently) the A16 chip is using ARMv9. What advantages that actually means in practice remains to be seen, but ARMv9 has these major new security and AI/ML features - from https://www.arm.com/blogs/blueprint/armv9
The Arm Confidential Compute Architecture (CCA) builds on the foundations of Arm TrustZone by enabling, for example, your personal banking information to be fully separated from your smartphone’s social media applications. Arm CCA’s new security features mean that even if a social media app did become infected with malware, it could not spread to the rest of your device.
Staying with security, the Arm Memory Tagging Extension (MTE) will be an integral part of the first generation Armv9-A based processors. Memory corruption is a major tool in a hacker’s inventory: many well-publicized data security breaches of the past 30 years have resulted from exploiting vulnerabilities in how computers store and recall data from memory. If a hacker knows the location of an important string of data, they can overwrite it with malicious code.
Enhanced parallel compute with Scalable Vector Extension 2 for Armv9
We’re also enhancing the performance of the v9 instruction set by upgrading our Scalable Vector Extension technology. SVE is already used in the Arm-based Fujitsu A64FX chip now powering the world’s fastest supercomputer, Fugaku and the Isambard 2 Arm-based supercomputer housed at the UK’s Meteorological Office.
With Armv9’s SVE2 upgrade, chip designers can choose a vector length in multiples of 128, up to 2048 bits. That’s an enormous amount of parallel compute, and while SVE was initially developed for the HPC space, SVE2 in Armv9 extends SVE support for a range of specialized DSP and XR (augmented and virtual reality) workloads, from genomics to computer vision… In Armv9, SVE2 also opens up a range of new approaches to deploying more powerful AI.