I haven't seen any recent benchmarks, but ones from 2011 all seemed to show CUDA and OpenCL on open footing in terms of performance when optimised properly.[1][2] CUDA simply had better library support, and a more well defined and uniform architecture to target. Whereas OpenCL is likely to require more programming to fill in the gaps for library support, and different optimisations depending on the architecture you wish to target. I'm guessing since then, the CUDA compiler may have improved somewhat in terms of optimisation based on some micro-benchmarking research I was looking the at the other day.

There's also Intel's MIC to consider now to, although that has a vastly different architecture to GPU. Again performance was similar between MIC and GPU in 2013[3], each performing better where their architecture was more suited, GPUs were capable of providing double the bandwidth for random access data.

In terms of AMD vs NVIDIA, I've not looked into it, I doubt AMD has anything to really compete with NVIDIAs current GPU accelerated compute lines. However again there was always that distinction (re bitcoin?) that AMD cards have better integer arithmetic and NVIDIA better float arithmetic.

Disclaimer: I use CUDA in my research, never tried OpenCL.

[1] http://arxiv.org/abs/1005.2581

[2] http://ieeexplore.ieee.org/xpl/login.jsp?tp=&arnumber=604719...

[3] http://arxiv.org/abs/1311.0378