thanks I do appreciate it! The local mode depends heavily on the hardware and the model you choose.
I run it exclusively in local mode nowadays. Old Macbook Pro with M1 chip with 32g ram + Model Large v3 Turbo.
Transcribing one minute of audio takes around 2-3 seconds, compared to the 0.5 to 1 second if using the openAI API.
For my usecase this a no brainer. Not having to pay + keeping all of my data private is well worth waiting 1.5 seconds longer. Also I simply think it is pretty cool to run models locally, so there that :D
Feel free to try it out completely for free and lmk your thoughts!
Hey HN,I built VibeWhisper because I was using Claude Code all day and the bottleneck wasn't thinking — it was typing. I tried an existing voice-to-text tool, loved the workflow, then saw the price: $20/month for a thin wrapper around OpenAI Whisper where 10 minutes of API usage costs $0.06. So I built my own in a weekend.How it works: Hold a configurable global hotkey (default: Right...
You are right, if you share the link and the password via the same (possibly compromised) channel, you are still at risk.
It is still mostly fine if you set the self-destruct to 1 successful download and your coworker acts within minutes.
It would be better if you verbally communicate the password in a e.g. a stand up call ("Guys, password is <InsertProjectName>+<CoworkerName>").
Second best would be 2 different channels Link per Slack Password per SMS
Best option: Just tell your coworker to setup an account himself and send him a direct transfer. End2End encrypted, asymmetricaly using his public key.
Hey everyone, English is not my native language. This post was polished with AI, but the content is mine.I run a small dev agency in Germany. Every week someone shares database credentials, API keys, or a .env file via Slack or email. Not because they don’t care: because there’s no frictionless alternative.Vault setups are heavy. Enterprise tools are expensive. I just needed: upload → share...
https://gpt-watermark-remover.com/
Hi HN, I’m Aleksandar (founder @ The CodeCave GmbH).I built GPT Watermark-Remover because I needed a fast, private way to clean AI-generated artifacts out of my drafts.What it doesDetects zero-width spaces, soft-hyphens and other invisible AI watermarks in text (up to 2 000 chars) entirely client-side Highlights all found markers and removes them with one click Lets you copy the cleaned text...