Selfhosted

Any NPU/TPU you can buy is going to be essentially useless for either image diffusion or LLMs. The onboard RAM is both far too small and far too slow (LLM text generation speed relies on RAM speed first and foremost, and both LLMs and image models tend to be, you know, big), and USB isn't nearly fast enough to help with that, not to mention that software support is pretty much nonexistent. You'd be better off upgrading the GPU to a 3060ti 12gb or something.

P.S. A word of advice, consider using something other than Ollama. Llama.cpp in router mode or llama-swap support pretty much all of the functionality that Ollama does without being crap. Ik_llama.cpp is also nice if you have a CPU/Nvidia setup.

If you wanna make the most out of what you've got now, the LFM2.5 series of LLMs are quite good for the small size and fast inference speeds with sizes ranging from 0.2 billion to 8 billion parameters, though their low parameter count means that you'll probably wanna hook them up to some sort of web search or similar since they won't have a ton of general knowledge.

If you have at least 32GB of RAM, Qwen3.6 35B is quite a good general-purpose model that runs faster than its parameter count would suggest.

Aren't diffusion models and LLMs (ollama) too big for an external NPU? As far as I know something like a Coral runs specific models only. And it's limited to the 1 or maybe 2GB of memory on it. It'd do tasks like voice recognition, or image classification. But not generate images or text.

If you want to run arbitrary AI models and generative AI, I think you should be looking for a graphics card?!