Big fan of Salvatore's voxtral.c and flux2.c projects - hope they continue to get optimized as it'd be great to have lean options without external deps. Unfortunately it's currently too slow for real-world use (AMD 7800X3D/Blas) when adding Voice Input support to llms-py [1].
In the end Omarchy's new support for voxtype.io provided the nicest UX, followed by Whisper.cpp, and despite being slower, OpenAI's Whisper is still a solid local transcription option.
Also very impressed with both the performance and price of Mistral's new Voxtral Transcription API [2] - really fast/instant and really cheap ($0.003/min), IMO best option in CPU/disk-constrained environments.
[1] https://llmspy.org/docs/features/voice-input
[2] https://docs.mistral.ai/models/voxtral-mini-transcribe-26-02
+1 for voxtype with Whisper-base model it is quite fast an accurate
One thing I keep looking for is transcribing while I'm talking. I feel like I need that visual feedback. Does voxtype support that?
(I wasn't able to find anything at glance)
Handy claims to have an overlay, but it seems to not work on my system.
Hi! This model is great, but it is too big for local inference, Whisper medium (the "base" IMHO is not usable for most things, and "large" is too large) is a better deal for many environments, even if the transcription quality is noticeable lower (and even if it does not have a real online mode). But... It's time for me to check the new Qwen 0.6 transcription model. If it works as well as their benchmarks claim, that could be the target for very serious optimizations and a no deps inference chain conceived since the start for CPU execution, not just for MPS. Since, many times, you want to install such transcription systems on server rent online via Hetzner and other similar vendors. So I'm going to handle it next, and if it delivers, really, time for big optimizations covering specifically the Intel, AMD and ARM instructions sets, potentially also thinking at 8bit quants if the performance remain good.