In the year 2000, a M1 MacBook Air would have been the world's fastest supercomputer (or second fastest if you had the base model with the 7-core GPU).
Impressive, of course; but not quite that impressive.
Only true if all you're running is matmul (supercomputer has general purpose CPUs so more flexible than M1 GPU) - also those flops are probably FP64 in supercomputer ratings and FP32 in M1.
As a smart man I knew used to say, supercomputers are about I/O not raw compute. Those have terabytes of RAM not 8GB.
Your question hits directly at latency vs. throughput distinction. Depends on which you mean by "fast."
Throughput-wise, the supercomputer is competitive because it has a lot of local RAM connected to lots of independent nodes, which, in aggregate, is comparable to modern laptop's RAM throughput (still much more than disk) with a caveat, that you can only leverage the supercomputer bandwidth if your workload is embarrassingly parallel running on all nodes[1]. Latency-wise, old RAM still beats NVMe by two or three orders of magnitude.
[1]: there's another advantage that supercomputer has which is lots more of local SRAM caches. If the workload is parallel and can benefit from cache locality, it blows away the modern microprocessor.
Only true if all you're running is matmul (supercomputer has general purpose CPUs so more flexible than M1 GPU) - also those flops are probably FP64 in supercomputer ratings and FP32 in M1.
As a smart man I knew used to say, supercomputers are about I/O not raw compute. Those have terabytes of RAM not 8GB.