It's not fixed and our chip wasn't designed with LLMs in mind. It's a general purpose, low latency, high throughput compute fabric. Our compiler toolchain is also general purpose and can compile arbitrary high performance numerical programs without the need for handwritten kernels. Because of the current importance of ML/AI we're focusing on PyTorch and ONNX models as input, but it really could be anything.

We can also deploy speech models like Whisper, for example, or image generation models. I don't know if we have any MOE architectures, but we'll be implementing Mixtral soon for sure!