[✨ FEATURE] Remote transcription backend with the ability to run the speech-to-text model on a separate machine

[salimhamed]

Problem

All of FluidVoice's speech engines run on-device. The SpeechModel catalog (FluidAudio/CoreML Parakeet, Qwen3, Cohere, Nemotron, Apple Speech, whisper.cpp) is exclusively local, and every
TranscriptionProvider implementation loads and executes the model on the Mac running the client.

This means transcription quality and latency are capped by the hardware of the machine you're dictating on. As a result, users cannot:

• Use a lightweight or older Mac (including Intel Macs, which are locked out of all the Apple Silicon–only FluidAudio models) as the dictation client while a more powerful machine on the
  LAN does the inference.
• Run a single larger, higher-accuracy model (e.g. Whisper Large, or a GPU-served model) on a home server and share it across several Macs.

The built-in local API server exposes POST /v1/transcribe, so a FluidVoice instance can already serve transcriptions, but it binds only to 127.0.0.1, and the app has no way to consume a remote transcription endpoint.

The AI-enhancement layer already supports custom OpenAI-compatible base URLs for the post-processing LLM, so remote inference is an established pattern in the app, just not for speech to text.

Proposed solution

Add a "Remote server" speech engine option alongside the existing local models:

1. New TranscriptionProvider implementation that sends captured audio to a user-configured HTTP endpoint and returns the transcript.
2. Settings UI under Speech Recognition, including: base URL, optional API key, model name, and a "Test connection" button. This mirrors the custom-endpoint UX that already exists for AI post-processing providers.
3. Wire format would support the OpenAI-compatible POST /v1/audio/transcriptions (multipart WAV upload) so the feature works out of the box with the broad ecosystem of self-hostable servers (e.g., whisper.cpp server, faster-whisper/speaches, LocalAI, vLLM, ONNX/NIM Parakeet servers, etc.)
4. Optionally, allow the existing built-in local API server to bind to a LAN interface (opt-in, with an API token). This would allow one FluidVoice install on a powerful Mac to act as the transcription backend for other FluidVoice clients.

Streaming preview can be out of scope for a first version.

Alternatives considered

No response

[altic-dev]

You can port forward from the mac to any other PC and work on it. do you want to ping from other device?

[salimhamed]

You can port forward from the mac to any other PC and work on it. do you want to ping from other device?

@altic-dev Thanks for the quick reply! I think that's the reverse direction of what I'm asking for.

Port-forwarding would let other devices call the Local API on my Mac, using my Mac as the transcription server.

What I'm asking for is the opposite. I want the Mac running the FluidVoice client to offload the STT inference to a different, more powerful machine, and receive the transcript back.

Here's my concrete use case: I dictate on a MacBook Air running FluidVoice. On my LAN, I have a server with a dedicated GPU running an OpenAI-compatible transcription endpoint. I want FluidVoice to route dictation audio to this external endpoint instead of running inference on the client Mac.

I was thinking this could just be a "Remote server (custom endpoint)" option in the speech model picker, similar to how custom OpenAI-compatible providers already work for AI post-processing.

[grohith327]

Hey @salimhamed, a couple of things:

1. There is a transcribe route in the app right now but its not fully built out, you can't start the server directly from the app GUI but we are looking to build this change this. Make it easier to run the transcription/post-processing server
2. Right now since we are a Mac app, our backend is in Swift and the models use CoreML. We have a windows/linux version coming out soon that should leverage any GPU

Once these two are in, you should be able to achieve what you are looking for.

[salimhamed]

Hi @grohith327, thanks for the reply and details about your roadmap.

The two roadmap items you mentioned are focused on running FluidVoice's transcribe server independently and a Windows/Linux build that could run on custom hardware. Those would let me stand up a FluidVoice instance as the backend on my linux server with a dedicated GPU, which is great.

However, the functionality I'm asking for is slightly different. I'm asking for a client side option, in the Mac app's speech model picker, to route dictation audio out to a configurable endpoint (base URL + optional API key) that is compatible with the OpenAI /v1/audio/transcriptions format. This would let me self-host a transcription backend that is compatible with FluidVoice.

This would decouple model choice from the models bundled with the app. Users could run any model served behind the OpenAI transcription API without waiting for each to be packaged into a release.

Is this client-side "remote endpoint" option something you'd be open to?

[altic-dev]

So plug in any voice model. Cloud/remote just like LLMs in Enhancement session?

…

On Wed, Jul 8, 2026 at 10:19 AM Salim ***@***.***> wrote: *salimhamed* left a comment (altic-dev/FluidVoice#547) <#547 (comment)> Hi @grohith327 <https://github.com/grohith327>, thanks for the reply and details about your roadmap. The two roadmap items you mentioned are focused on running FluidVoice's transcribe server independently and a Windows/Linux build that could run on custom hardware. Those would let me stand up a FluidVoice instance as the backend on my linux server with a dedicated GPU, which is great. However, the functionality I'm asking for is slightly different. I'm asking for a client side option, in the Mac app's speech model picker, to route dictation audio out to a configurable endpoint (base URL + optional API key) that is compatible with the OpenAI /v1/audio/transcriptions format. This would let me self-host a transcription backend that is compatible with FluidVoice. This would decouple model choice from the models bundled with the app. Users could run any model served behind the OpenAI transcription API without waiting for each to be packaged into a release. Is this client-side "remote endpoint" option something you'd be open to? — Reply to this email directly, view it on GitHub <#547?email_source=notifications&email_token=BVSOW2QTJQ7I65MKDJSAY5L5DZ7DPA5CNFSNUABFM5UWIORPF5TWS5BNNB2WEL2JONZXKZKDN5WW2ZLOOQXTIOJRG4ZTQNRZGIYKM4TFMFZW63VHNVSW45DJN5XKKZLWMVXHJLDGN5XXIZLSL5RWY2LDNM#issuecomment-4917386920>, or unsubscribe <https://github.com/notifications/unsubscribe-auth/BVSOW2VUXIDDDX3IVIMXQZ35DZ7DPAVCNFSNUABGKJSXA33TNF2G64TZHMYTANRRGMZDOMZRGE5US43TOVSTWNBYGMYTEMBWHA2DDILWAI> . You are receiving this because you were mentioned.Message ID: ***@***.***>

[salimhamed]

@altic-dev that's exactly right. For my specific use-case, I want to locally host a voice model on linux server with a powerful GPU on my LAN, then point FluidVoice at it. This will free up resources on my Mac and allow me to experiment with other voice models.

[grohith327]

Haven't thought about FluidVoice being client only, you love our interface that much huh 😅. Fair ask

[salimhamed]

you love our interface that much huh

It's just that good! ;)