It is optimized for compatibility across different APIs as well as has specific hardware builds for AMD GPUs and NPUs. It’s run by AMD.
Under the hood they are both running llama.cpp, but this has specific builds for different GPUs. Not sure if the 9070 is one, I am running it on a 370 and 395 APU.
Lemonade is using llama.cpp for text and vision with a nightly ROCm build. It can also load and serve multiple LLMs at the same time. It can also create images, or use whisper.cpp, or use TTS models, or use NPU (e.g Strix Halo amdxdna2), and more!
In my experience using llama.cpp (which ollama uses internally) on a Strix Halo, whether ROCm or Vulkan performs better really depends on the model and it's usually within 10%. I have access to an RX 7900 XT I should compare to though.
From what I understand, ROCm is a lot buggier and has some performance regressions on a lot of GPUs in the 7.x series. Vulkan performance for LLMs is apparently not far behind ROCm and is far more stable and predictable at this time.
I was talking about ROCm vs Vulkan. On AMD GPUs, Vulkan has been commonly recognized as the faster API for some time. Both have been slower than CUDA due to most of the hosting projects focusing entirely on Nvidia. Parent post seemed to indicate that newer ROCm releases are better.
