shubham2802
shubham2802 on Hacker News
my earlier reply was too glib. Even though the key had no usable balance, it still should not have been exposed. We’re removing it now and fixing the demo flow so this doesn’t happen again. Thanks for calling it out.
Cheers!
I see, sure will fix it asap.
Again, thanks for feedback.
I am pretty sure we don't have balance. It's a bait :)
Will look into it.
Yes, would love to chat
It does tries to have some memory management done too - to remember previous context + some auto compact feature.
Additionally, personality feature - try it out!! Super fun :)
Yes, we do have plans to support it.
RunAnywhere builds software that makes AI models run fast locally on devices instead of sending requests to the cloud.
Right now, our focus is Apple Silicon.
Today there are two parts:
MetalRT - our proprietary inference engine for Apple Silicon. It speeds up local LLM, speech-to-text, and text-to-speech workloads. We’re expanding model coverage over time, with more modalities and broader support coming next.
RCLI - our open-source CLI that shows this in practice. You can talk to your Mac, query local docs, and trigger actions, all fully on-device.
So the simplest way to think about us is:
we’re building the runtime / infrastructure layer for on-device AI, and RCLI is one example of what that enables.
Longer term, we want to bring the same approach to more chips and device types, not just Apple Silicon.
For people asking whether the speedups are real, we’ve published our benchmark methodology and results here:
LLM: https://www.runanywhere.ai/blog/metalrt-fastest-llm-decode-e...
Speech: https://www.runanywhere.ai/blog/metalrt-speech-fastest-stt-t...
Sorry about that but this is what is being there in github : Apple M3 or later required. MetalRT uses Metal 3.1 GPU features available on M3, M3 Pro, M3 Max, M4, and later chips. M1/M2 support is coming soon. On M1/M2, RCLI automatically falls back to the open-source llama.cpp engine.
Just need some few days to have our catalog of models out soon!!
Fully local - no data is collected!!