Running bytecode directly on hardware has certainly been tried (e.g. ARM's Jazelle).
In today's world this is generally not great.
Interpreted languages often include bytecode instructions that actually do very complex things and so do not nicely map to operations that can be sanely implemented in hardware. So you end up with all the usual boring alu, branch etc operations implemented in hardware, and anything else traps and runs a software handler.
Separately, interpreted language bytecode is often a poor fit for hardware execution; e.g. for dotnet (and python) bytecode many otherwise trivial operations do not explicitly encode information about types, and therefore the hardware must track type information in order to do the right thing (floating point addition looks very very different from integer addition!)
A lot of effort has been spent on compiler optimisation for x86 and ARM code. JIT compilers benefit massively from this. Meanwhile, interpreted language bytecode is often very lightly optimised, where it is optimised at all (until relatively recently, explicit Python policy as set by Guido van Rossum was to never optimise!) Optimisation has the side effect of throwing away potentially valuable high level / semantic information; optimising at the bytecode level hinders debuggability for interpreted code (which is a primary goal in Python) and can also be detrimental to JIT output; and the results are underwhelming compared to JIT since your small team of plucky bytecode optimisers isn't really going to compete with decades of x86 compiler development; and so the incentive is to not do much of that.
So if you're running bytecode in hardware, on top of all the obvious costs, you are /running unoptimised code/. This is actually the thing that kills these projects - everything else can ultimately be solved by throwing more silicon at it, but this can only really be solved by JITting, and the existing JIT+x86 / JIT+ARM solution is cheap and battle tested.
I understand that is the reason Lisp Machines were dropped (even in the time where Lisp was still a very good seen language). At least I understand so in the SICP videos, like in 1986 it was already clear it was much better to compile to ASM.
In today's world this is generally not great.
Interpreted languages often include bytecode instructions that actually do very complex things and so do not nicely map to operations that can be sanely implemented in hardware. So you end up with all the usual boring alu, branch etc operations implemented in hardware, and anything else traps and runs a software handler.
Separately, interpreted language bytecode is often a poor fit for hardware execution; e.g. for dotnet (and python) bytecode many otherwise trivial operations do not explicitly encode information about types, and therefore the hardware must track type information in order to do the right thing (floating point addition looks very very different from integer addition!)
A lot of effort has been spent on compiler optimisation for x86 and ARM code. JIT compilers benefit massively from this. Meanwhile, interpreted language bytecode is often very lightly optimised, where it is optimised at all (until relatively recently, explicit Python policy as set by Guido van Rossum was to never optimise!) Optimisation has the side effect of throwing away potentially valuable high level / semantic information; optimising at the bytecode level hinders debuggability for interpreted code (which is a primary goal in Python) and can also be detrimental to JIT output; and the results are underwhelming compared to JIT since your small team of plucky bytecode optimisers isn't really going to compete with decades of x86 compiler development; and so the incentive is to not do much of that.
So if you're running bytecode in hardware, on top of all the obvious costs, you are /running unoptimised code/. This is actually the thing that kills these projects - everything else can ultimately be solved by throwing more silicon at it, but this can only really be solved by JITting, and the existing JIT+x86 / JIT+ARM solution is cheap and battle tested.