Performance is subject to debate and quality of implementation and whether such implementations will ever be financed and made ...
But *code size* is a demonstrable fact.
RISC-V has by far the most compact code of any popular 64 bit ISA, and that was true even of RV64GC. The gap has only widened with RVA23.
Just load up your favourite OS (e.g. Ubuntu 26.04) for various ISAs in Docker and compare the `text` size of various binaries, individually or in aggregate.
In 32 bit ARMv7-M / ARMv7-A had a small code size lead over RV32IMAC, but this is reversed in modern RISC-V e.g. if you look at RISC-V Hazard3 vs Arm Cortex-M33 in the RP2350 (Raspberry Pi Pico 2) where you can trivially change one option setting in your project and recompile and test.
The only exception is that the M33 has a single-precision FPU, which neither the Hazard3 nor the Cortex-M0+ in the RP2040 have.
> RISC-V has by far the most compact code of any popular 64 bit ISA,
Forgot to say “RISC”. Cause else: amd64
That is false.
All the claims of the RISC-V fans that I have seen in the past compared the compressed variant of RISC-V with the uncompressed variants of the other ISAs.
Most other ISAs, like ARM, POWER and MIPS, also have compressed variants and if RISC-V were compared with those, it would lose.
Moreover, if you use safe compilation options with RISC-V, the code size explodes in comparison with any other ISA, because I am not aware of any other ISA introduced after 1974 that lacks hardware overflow detection, which multiplies by 3 or more the number of arithmetic instructions required for any computation.
This is a new claim that I see now, that RISC-V can be more compact than Cortex-M33 (i.e. where both use a compressed encoding), which I find unbelievable, because if I assembly by hand almost any function that is not too simple I can make it shorter on Cortex-M33 than on RISC-V and I doubt that the current compilers are so bad that they generate much worse code.
RISC-V is shorter on any code that has a lot of branches and negligible computations, but for anything more complex, with many computations and complex data structures, it loses.