In reality, the top end AMD 7970 has ~32 compute units, while ~$130 AMD 7770 has ~10 compute units. Each compute unit can has 4 SIMD units, each SIMD unit executes 16 single-point floating operations per clock, from a pool of 16 "hyperthread-like" work-items that are queued up. (Total of 64 FLOPs per clock)
But... that is a bit difficult to say, now isn't it :-p
In comparison, Parallela's $99 unit has 16 discrete compute units, and their (unmade) higher-end offering will have 64 compute units. Both of which will operate with 2W of power.
Its a difference of scale. GPUs focus more on SIMD instructions, because graphics are innately matrix-based operations that very easily translate into SIMD. But if you are going to be doing unique operations per core (ie: lots and lots of branching on a single work-item), then Paralella's approach would give better performance.
So... yes... I over-simplified earlier, and got a few numbers wrong. But the concept is the same. Epiphany has no SIMD units at all, and each core instead focuses entirely on single-threaded performance. (at best, 2 Floating Point operations per clock with the super-scalar architecture). This makes it slower in the strictest sense... but "more agile", and able to handle branches and conditionals better than the GPUs.
Also, remember that Epiphany works with only 2W of power... while a GPU like the AMD 7970 works with something like 300W of power. So of course, the 7970 is going to do more (especially with faster GDDR5 RAM and a PCIe x16 connection feeding it). So it isn't really a fair comparison there either.
Nonetheless, Epiphany does see a few situations where it might perform better than a classic CPU and better than a classic GPU. Its just a different software architecture, focusing on a different problem niche.