What parts/sections of a CPU take the biggest number of transistors?
From Quora.com:

How you spend your transistors really depends on the problem you're
trying to solve.
If you open up a 1 billion-transistor x86 processor, you'll see a
handful of very complex CPU cores, with many transistors dedicated to
decoding and scheduling instructions, predicting branches, and
managing virtual memory. You'll also see many transistors dedicated to
very fast cache memories. This mix of transistors reflect the general
purpose, varied workloads a typical Windows or Mac might encounter.
If you open up a 1 billion-transistor SPARC server processor, you'll
find a bunch of fairly simple in-order SPARC cores and a ton of cache.
These guys are optimized for many parallel database threads operating
on huge database working sets.
If you open up a 1 billion-transistor GPU processor, you'll see
hundreds of very specialized, deeply pipelined floating point compute
datapaths, fine-grain thread schedulers, and memory transfer engines
designed to stream texture, vertex and other data through the
processor efficiently. There isn't much branch control logic, but a
ton of matrix-friendly floating point compute hardware, along with RAM
to buffer the data as it passes through.
If you open up a 1 billion-transistor DSP optimized for cellular base
station applications (something I worked with in a previous job),
you'll find multiple dedicated signal processing blocks for handling
various over-the-air encoding protocols, a large network-accelerating
block for handling millions of packets whizzing through the device at
microsecond latencies, some highly capable general purpose DSPs
dedicating most of their transistors to multiply-accumulate
operations, and some ARMs to schedule everything. The transistors
there are split maybe 50-50 between compute/data movement and memory.
(Or maybe closer to 40-60.)
If you open up a 1 billion-transistor cell phone processor, you'll
find the most varied mix of all. You'll see a few general purpose ARM
processors (most likely), some GPUs, some video encode/decode
accelerators, maybe some DSPs, some networking peripherals, and many
other peripherals for managing USB, Bluetooth, WiFi, and interfacing
to cameras, mics and speakers.
It all depends on what you're trying to do...

A billion transistors seems like a lot, but a trillion is now the record to beat, or at least a common ground to start from. Granted this is only for the most demanding applications. Analog and RF IC's have no desire to be so complex, not to mention the cost. The following blog is amazing that it happened so soon. From ExtremeTech.com

Cerebras Systems Unveils 1.2 Trillion Transistor Wafer-Scale Processor
for AI By Joel Hruska on August 20, 2019 at 9:00 am
Modern CPU transistor counts are enormous — AMD announced earlier this
month that a full implementation of its 7nm Epyc “Rome” CPU weighs in
at 32 billion transistors. To this, Cerebras Technology says: “Hold my
beer.” The AI-focused company has designed what it calls a Wafer Scale
Engine. The WSE is a square, approximately eight inches by nine
inches, and contains roughly 1.2 trillion transistors.
I’m genuinely surprised to see a company bringing a wafer-scale
product to market this quickly. The idea of wafer-scale processing has
attracted some attention recently as a potential solution to
performance scaling difficulties. In the study we discussed earlier
this year, researchers evaluated the idea of building an enormous GPU
across most or all of a 100mm wafer. They found that the technique
could product viable, high-performance processors and that it could
also scale effectively to larger node sizes. The Cerebras WSE
definitely qualifies as lorge large — its total surface area is much
larger than the hypothetical designs we considered earlier this year.
It’s not a full-sized 300mm wafer, but it’s got a higher surface area
than a 200mm does.
The largest GPU, measures 815 square millimeters and packs 21.1B
transistors. So the Cerebras WSE is just a bit bigger, as these things
go. Some companies send out pictures of their chips held up next to a
diminutive common object, like a quarter.