When I see a little AI tool answering questions properly, my first thought is: “So, it’s ready to use, right?” But making it available for other people is another matter. You have to take a fresh look at whether the connection is reliable and the access point is secure.
That’s exactly what caught my attention in @Acurast’s LLM tutorial. It explains how to run GGUF models on a phone Processor, use the built-in llama server for inference, and provide an OpenAI-compatible API. Apps that already use this kind of API may be able to connect directly to a model on a phone with just a few configuration changes.
The interesting part is that the tutorial uses localtunnel to make the model accessible from outside. The official guide itself warns that this example isn’t secure and shouldn’t be deployed as-is. The model is running and the API works, but security is only the beginning. That’s a pretty practical reminder.
I later found that #Acurast has a separate Tunnel guide, which uses a reverse tunnel to let external users access services on a phone. It supports HTTPS and lets you verify your own domain. This is a different approach from localtunnel in the older tutorial. Even with HTTPS, you still need to check the app’s own authentication and access permissions, one by one.
I really like that the official guides are upfront about these limitations. Being able to run AI models on a phone is already pretty exciting, but there are plenty of details to work through between a working example and something people can use reliably over the long term. Ordinary users just want something that works as soon as they open it—they shouldn’t have to worry about whether the connection point is secure.
👉 https://hub.acurast.com/rebellion?ref=apksoh
That’s exactly what caught my attention in @Acurast’s LLM tutorial. It explains how to run GGUF models on a phone Processor, use the built-in llama server for inference, and provide an OpenAI-compatible API. Apps that already use this kind of API may be able to connect directly to a model on a phone with just a few configuration changes.
The interesting part is that the tutorial uses localtunnel to make the model accessible from outside. The official guide itself warns that this example isn’t secure and shouldn’t be deployed as-is. The model is running and the API works, but security is only the beginning. That’s a pretty practical reminder.
I later found that #Acurast has a separate Tunnel guide, which uses a reverse tunnel to let external users access services on a phone. It supports HTTPS and lets you verify your own domain. This is a different approach from localtunnel in the older tutorial. Even with HTTPS, you still need to check the app’s own authentication and access permissions, one by one.
I really like that the official guides are upfront about these limitations. Being able to run AI models on a phone is already pretty exciting, but there are plenty of details to work through between a working example and something people can use reliably over the long term. Ordinary users just want something that works as soon as they open it—they shouldn’t have to worry about whether the connection point is secure.
👉 https://hub.acurast.com/rebellion?ref=apksoh