Scroll to the "Cinebench 2024 Single Power Efficiency" section.[0]
It doesn't even beat Lunar Lake in efficiency (made on TSMC N3B) released in 2024.
[0]https://www.notebookcheck.net/Intel-Panther-Lake-Core-Ultra-...
From the article you linked:
> With the new Panther Lake mobile processors, Intel has managed to successfully combine the two previous generations, Arrow Lake and Lunar Lake, as the performance is even better than with Arrow Lake, while efficiency has been improved at the same time. Even with low power limits, the performance is very competitive, and Intel (in conjunction with the new GPUs) is therefore the better choice for slim laptops.
Besides the fact that Lunar Lake has a lower consumption in the memory interface, which has nothing to do with the fabrication process, single-thread benchmarks cannot be used to compare CPU fabrication processes.
Both the absolute performance and the performance per watt in single-thread benchmarks are determined mainly by the CPU design and they are only slightly constrained by the CPU fabrication process.
Only the multithreaded benchmarks are useful for comparing CMOS fabrication processes, because the performance in multithreaded benchmarks (with a given cooling system) is limited mainly by the energy required to switch a logic gate, which is a characteristic of the fabrication process, and they are only weakly dependent on the CPU design, as long as the CPU design does not have obvious mistakes.
In multithreaded benchmarks, CPUs work at a fixed power consumption, determined by the maximum allowable temperature and the cooling system. A fixed power means a fixed number of gates that switch per second. The completion of a given benchmark requires a similar number of gate switchings in well designed CPUs, in which case the performance in such a benchmark is fully determined by the fabrication process. Deviations from proportionality appear when some CPUs need much less gate switchings than others to complete some work, which happens for example when a CPU has wider vector or matrix execution units, e.g. by supporting AVX-512 or SME or AMX.