With Metal Performance Shaders we have absolute control over pixels and direct access to the underlying hardware. For us that means we can rapidly test and deploy new CoreML models and also the ability to quickly respond to any feature-request.
So this was my point in bringing it up: "We're faster than the other APIs out there" is a much more direct benefit to communicate to me as an API user than "We use GPUs, which makes us fast, faster than the competition, who don't use GPUs". The latter version has me making assumptions and eventually getting to a conclusion that matters to me; why not take me there immediately?
The thing is, as a non-expert in this area, I don't even fully understand whether the real performance bottleneck in such an API is the latency of uploading the image and downloading the result, or the computational processing of the image. So if using GPUs cuts the overall request time by 70%, that's great! If it only affects the round-trip time by 5%, then it's not a huge deal to me. As the domain expert, I'm relying on Pixaven's marketing to educate me on this.
Here's what I don't quite get: why does the GPU differentiation matter to me as a user of your API? I get that you're faster than doing it myself using something like ImageMagick, but are you faster than the other image processing APIs out there because of this? If so, that's what I think you should be touting. If not, whether the images are being processed by GPUs or trained giraffes is not that important to me as a consumer of the API, but I could be way off-base.