Perhaps you are meaning to compare transistors with neurons? If we do that, then yes, a transistor is a lot simpler than a neuron. But transistors are also insanely fast compared to neurons, so transistors do far FAR more, per unit of time.
A bee brain might have a million neurons, operating at maximum speed of about 250 Hz.
10^6 neurons x 250 Hz
= 2.5 x 10^8 Hz for a bee brain.
We can easily model that many neurons with a trillion transistors, operating at 100 Ghz. (If that sounds fast to you, keep in mind that CPU clock speeds account for many transistors switching in series.)
10^12 transistors x 10^11 Hz
= 10^23 Hz for a CPU
That is a factor of 4 x 10^14 more powerful.
So yeah, the only problem for modeling a bee brain is identifying the organization of its neurons.
Nature does a lot with a little. Trillions of bee life years went into designing a really efficient bee brain.
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Atoms:
A bee brain might have 10^20 atoms. Atoms interact at speeds that are far beyond anything we are talking about here. But they don't "switch", they bounce around every which way and slowly end up reacting when they connect with the right conditions. This is called Brownian motion and its not computation, its natures way of using the chaos produced by heat to give compounds so many chances to find their right context that they eventually do.
While we could not easily model that many atoms, nobody wants to (with regard to bees). Atoms are neither the "transistors" or the neurons of a bee brain.
