k9294

I'm founder of ottex.ai, I use stt pretty much all the time when work with AI and quite often for communications to draft emails and chat messages.

I started ottex half a year ago after I tested gemini 2.5 flash native audio support. I was blown away by the quality of transcripts and decided to built an app to use it myself.

Currently the default model in the app is Gemini 3 flash, but you can connect to 9 providers and God knows how many models to play with.

I would suggest you to try this models for ai prompting:

- Gemini 3 / 3.5 flash - Soniox rtt v5 - Mistral transcribe v2 - assembly 3.5 pro

Meh... Waiting for OpenAI models without this 5 more days subscription bullshit.

It looks like Anthropic baiting people into Max subscriptions before turning the model off. No thank you.

What are some cool random things you've learned?

// you == the reader of this comment

What about request caching? If you swap to a cheaper model mid execution it might cost more that to make multiple requests to the already cached provider?

+1 for Go! it's my go-to language for any new project at the moment. It's simple, idiomatic, has no awaits, fast compile times, static typing, and it is very opinionated, which helps a lot because agents "subconsciously" follow these standards. Comparing it to TS, it's like day and night; a TS codebase rots at the speed of light...

I also created a guardrails library (inspired by Java's ArchUnit) to prevent code rot - https://github.com/ksanderer/goarch. It helps enforce code standards, decouple the codebase, prevent cross-module imports and crashes builds with concise error messages for agents to fix problems early, very nice experience

Working on https://ottex.ai - voice ai for busy professionals.

Think wisprflow + granola with 30+ top STT models under single login and pay as you go billing model with 25% markup over API.

What is yours agentic development experience with elixir? I used to like elixir a lot during a pre agentic era, but with coding agents it feels like the language isn't the best choice - slow compile time, weak type system (at least it was a year ago, I know there is work on that front), small ecosystem...

Small advice - make one repo “main” and link to it from the website instead of an organisation.

I wanted to star the project to track the progress but it feels a bit weird.. Which repo shall I track? Server? Cli? Sounds like a misc repos.

That's really cool!

One thing I'm confused with is how to create a shared resources like e.g. a redis server and connect to it from other vms? It looks now quite cumbersome to setup tailscale or connect via ssh between VMS. Also what about egress? My guess is that all traffic billed at 0.07$ per GB. It looks like this cloud is made to run statefull agents and personal isolated projects and distributed systems or horizontal scaling isn't a good fit for it?

Also I'm curious why not railway like billing per resource utilization pricing model? It’s very convenient and I would argue is made for agents era.

I did setup for my friends and family a railway project that spawns a vm with disk (statefull service) via a tg bot and runs an openclaw like agent - it costs me something like 2$ to run 9 vms like this.

Nope, but I will think about this, thank you for the idea. Maybe it's time to start a technical blog for ottex

There is no cold starts at all. It’s running non-stop.

Bunny bills per resource utilization (not provisioned) and since we run backend on Go it consumes like 0.01 CPU and 15mb RAM per idle container and costs pennies.

We at ottex.ai use bunny.net to deploy globally an openrouter like speach-to-text API (5 continents, 26 locations, idle cost 3$).

Highly recommend their Edge Containers product, super simple and has nice primitives to deploy globally for a low latency workloads.

We connect all containers to one redis pubsub server to push important events like user billing overages, top-ups etc. Super simple, very fast, one config to manage all locations.

Anecdotally, I’ve been seeing a lot of weird behavior from Opus when it decides, mid-execution, to switch to a different "simpler" solution, and that really pissed me off.

At one point, I carefully designed a spec document, forced Opus to reread it, create a plan with the planning tool that followed the spec, and use the task tool to track the implementation... AND AFTER OPUS READS THE FIRST FUCKING FILE, it says, "Oh, there are missing dependencies in project X. It’ll be hard to add them, so I’m going to throw away the whole plan and just do a simple fix..."

After that, I canceled my $200 Max plan, which I’d been subscribed to since June 2025, and decided to check out Codex

Try ottex.ai - it has an OpenRouter like gateway with most STT models on the market (Gemini, OpenAI, Groq, Deepgram, Mistral, AssemblyAI, Soniox), so you can try them all and choose what works best for you.

My favorites are Gemini 3 Flash and Mistral Voxtral Transcribe 2. Gemini when I need special formatting and clean-up, and Voxtral when I need fast input (mostly when working with AI).

It's actually a nice idea - an always-on micro AI agent with voice-to-text capabilities that listens and acts on your behalf.

Actually, I'm experimenting with this kind of stuff and trying to find a nice UX to make Ottex a voice command center - to trigger AI agents like Claude, open code to work on something, execute simple commands, etc.

I've been experimenting with Gemini 3.1 Flash Lite and the quality is very good.

I haven't found official benchmarks yet, but you can find Gemini 3 Flash word error rate benchmarks here: https://artificialanalysis.ai/speech-to-text/models/gemini — they are close to SOTA.

I speak daily in both English and Russian and have been using Gemini 3 Flash as my main transcription model for a few months. I haven't seen any model that provides better overall quality in terms of understanding, custom dictionary support, instruction following, and formatting. It's the best STT model in my experience. Gemini 3 Flash has somewhat uncomfortable latency though, and Flash Lite is much better in this regard.

You can test Gemini 3.1 Lite transcription capabilities in https://ottex.ai — the only dictation app supporting Gemini models with native audio input.

We benchmarked it for real-life voice-to-text use cases:

                <10s    10-30s   30s-1m    1-2m    2-3m
  Flash         2548     2732     3177     4583    5961
  Flash Lite    1390     1468     1772     2362    3499
  Faster by    1.83x    1.86x    1.79x   1.94x   1.70x

  (latency in ms, median over 5 runs per sample, non-streaming)

- 1.8x faster than Gemini 3 Flash on average

- ~1.4 sec transcription time for short to medium recordings

- ~$0.50/mo for heavy users (10h+ transcription)

- Close to SOTA audio understanding and formatting instruction following

- Multilingual: one model, 100+ languages

Gemini is slowly making $15/month voice apps obsolete.

Gemini 3.1 Flash-Lite is our most cost-efficient Gemini model, optimized for low latency use cases for high-volume, cost-sensitive LLM traffic.

It provides a significant quality increase over Gemini 2.0 Flash-Lite and Flash-Lite models, matching Gemini 2.5 Flash performance across key capability areas:

Improved response quality: Aims to match 2.5 Flash performance and align with target Flash-Lite use cases.

Improved instruction following: Targeted improvements to serve as a reliable migration path for complex chatbot and instruction-heavy workflows.

Improved audio input: Improved audio-input quality for tasks like Automated Speech Recognition (ASR).

Expanded thinking support: You can control how much reasoning the model performs by choosing from minimal, low, medium, or high thinking levels. This feature lets you balance response quality and speed for your specific use case.

---

Already available in Google AI Studio and OpenRouter

https://openrouter.ai/google/gemini-3.1-flash-lite-preview

Try ottex with Gemini 3 flash as a transcription model. I'm bilingual as well and frequently switch between languages - Gemini handles this perfectly and even the case when I speak two languages in one transcription.

You can try ottex for this use case - it has both context capture (app screenshots), native LLMs support, meaning it can send audio AND screenshot directly to gemini 3 flash to produce the bespoke result.

I'm building in the same space, Workin on https://ottex.ai - It's a free STT app, with local models and BYOK support (OpenRouter, Groq, Mistral, and more).

The top feature is the per-app custom settings - you can peak different models and instructions for different apps and websites.

- I use the Parakeet fast model when working with Claude Code (VS Code app). - And I use a smart one when I draft notes in Obsidian. I have a prompt to clean up my rambling and format the result with proper Markdown, very convenient.

One more cool thing is that it allows me to use LLMs with audio input modalities directly (not as text post-processing). e.g. It sends the audio to Gemini and prompts it to transcribe, format, etc., in one run. I find it a bit slow to work with CC, but it is the absolute best model in terms of accuracy, understanding, and formatting. It is the only model I trust to understand what I meant and produce the correct result, even when I use multiple languages, tech terms, etc.

Hey, I would really appreciate if you would try https://ottex.ai

I'm working on a Wispr/Spokenly competitor. It's free without any paywalled features, supports local models and a bunch of API providers including Mistral.

For local models ottex has - parakeet V3, Whisper, GLM-ASR nano, Qwen3-ASR (don't have voxtral yet though, looking into it).

btw, you can try new voxtral model via API (the model name to pick is `voxtral-mini-latest:transcribe`), I personally switched to it as my main default fast model - it's really good.

Hey, I would really appreciate if you will try https://ottex.ai

I'm working on a Wispr/Spokenly competitor. It's free without any paywalled features, supports local models and bunch of API providers including Mistral.

btw, the model name to pick is `voxtral-mini-latest:transcribe`, I personally switched to it as my main default fast model - it's really good.

Try https://ottex.ai/

I recently added support for Mistral provider, model is actually a very good one, I personally switched to it as my default model.

p.s. the app is free for personal user, has support for both local models and BYOK with OpenRouter, Groq, Mistral, Fireworks, and more coming soon.

Is there an oss model for next word / edits predictions for texts in general? e.g. Typing emails?

ottex.ai - free BYOK alternative to WisprFlow and Raycast AI shortcuts.

Native macOS and iOS apps with OpenRouter BYOK. Same quality as in proprietary products for 1-3$ per month instead of 35$.

I’ve worked with relatively large projects in TypeScript, Python, C#, and Swift, and I’ve come to believe the more opinionated the language and framework, the better. C# .NET, despite being a monster, was a breath of fresh air after TS. Each iteration just worked. Each new feature simply gets implemented.

My experience also points to compiled languages that give immediate feedback on build. It’s nearly impossible to stop any AI agent from using 'as any' or 'as unknown as X'casts in TypeScript - LLMs will “fix” problems by sweeping them under the rug. The larger the codebase, the more review and supervision is required. TS codebase rots much faster then rust/C#/swift etc.

Working on https://ottex.ai/ - BYOK alternative to Wispr Flow and Raycast AI shortcuts.

I love global voice-to-text transcription (especially when working with Claude Code or Cursor) and simple AI shortcuts like "Fix Grammar" and "Translate to {Language}".

I realized I was spending around €35/mo (€420 a year) on two apps for AI features that cost just pennies to run.

So I built Ottex - a native macOS app with a tiny footprint. Add your OpenRouter API key and get solid voice-to-text using Gemini 2.5 Flash, plus any OpenRouter model for AI shortcuts.

Building https://ottex.ai - a native MacOS app to solve repetitive micro tasks on a computer.

- Transcribe voice to text (especially useful when you need to explain something to Claude code )

- (soon) select text to instantly Check grammar / Improve writing / change tone of text

- (soon) select text to Translate between languages

I discovered that I have a few 10/20$ subscriptions (grammarly, raycast, wisperflow) that do embarrassingly simple stuff I can one shot with cheap SLM. So I decided to build a one app specialized in small repetitive tasks on computer.

They have a definition actually) “When AI generates $100 billion in profits” it will be considered an AGI. This term was defined in their previous partnership, not sure if it's still holds after the restructuring.

https://techcrunch.com/2024/12/26/microsoft-and-openai-have-...