Show HN: SlothSpeak: open-source BYO-API-K mobile chat with the best AI models

[SteveVeilStream]

Introducing SlothSpeak: An open-source, bring-your-own-API-keys, mobile app for voice chat with LLMs that prioritizes response quality over latency.

APK file available on GitHub in the releases. Currently only for Android. Is anyone interested in porting to iPhone?

My preferred way to interact with LLMs is talking and listening while I'm walking, biking, driving, etc. The problem with the apps from the frontier labs is that their voice mode prioritizes real-time interactions and so they use watered down models.

Even today with a paid subscription, ChatGPT Voice will tell you there are two r's in strawberry. The answers are also relatively brief and so there is a need to chain together a series of simpler requests when you want to do a deeper dive.

SlothSpeak goes to the opposite end of the spectrum. It might leave you hanging for a few minutes but when it gets back to you, it will be an answer from a state of the art model. You can even do deep research queries to get very long and comprehensive responses.

[herzigma]

This is great work. Most voice AI optimizes for latency - you made the opposite bet (quality over speed, frontier models over lightweight ones) and that's probably the right call.

The audio pipeline alone is impressive: on-device VAD, parallel TTS chunking, retry-from-failure mid-pipeline. That's not a weekend project; that's production-grade thinking.

Here's the thing that excites me most, though - the *cognitive layer* is wide open. The experience harness is solid, but right now every session starts cold. Persistent user memory, context that makes your 50th conversation meaningfully smarter than your first, light orchestration that turns a single question into a structured multi-step inquiry - that's likely where this goes next, and it's a compelling frontier.

Voice access to frontier reasoning is massively underserved. You've built the right foundation for it.

[SteveVeilStream]

Thanks. Adding memory is an interesting idea. I'd probably want to do it a little differently than what is done in the main apps to avoid overlap. I like the idea of being able to tag conversations and then use that "tag" to organize memory. E.g. You might want to have one set of conversations about fitness, another about travel, another about career, etc. with no overlap between them.