The answer is "maybe," but its not really measured in neurons at all.
There's 100 billion neurons in the human brain, give or take. A modern AMD Epyc 32 core processor weighs in at about 20 billion transistors. So 5 of them is on par with the brain, but we're clearly not at Artificial General Intelligences (AGI) yet!
So a transistor isn't a neuron. What can you do? Well, you can look at IBM's TrueNorth chips, which are designed to emulate the synapses of a brain. At the moment each chip has 256 million synapses. Estimates for number of synapses in the brain vary widely, but 150 trillion isn't a bad number. That means a mere 600 TrueNorth chips has the same number of synapses in the brain.
But what are you going to do with it? I can hand you 600,000 TrueNorth chips today, this very moment. Well, actually I can't, but IBM can. We can hook them together and have your neuron/synapse count today. They are very low power, so this would be easier than constructing many larger and more power hungry supercomputers. But does that help? When it comes to AI, it's the organization of the neurons that really matters. How do you configure the synapses. To this day, it is still unclear whether a computer can ever truly be more intelligent than an organic brain. The transhumanist in me wants to say it can, but science is still pulling back the veil on what it means to think. We can still be surprised.
By analogy, an empty hard drive, capable of storing 16,000,000,000,000 bytes of data is still just an empty platter. It's what you put in it that decides whether your hard drive is a collection of wisdom, or the world's largest collection of cat videos (Disclaimer: Cat videos may be the greatest source of wisdom on the planet. Disclaimer/Disclaimer: My cat may have been staring at me with murder in his eyes until I added that disclaimer)
If you really do want a numeric path towards AGI, I recommend reading up on Sentience Quotient (SQ). It was an approach which looked at the computational capacity of a brain versus its mass, and drew some conclusions about what might be required to think like a human. However, it's just numbers. The real question is can we make the patterns.