Fluid Inference

infra for ambient intelligence

[Fluid Inference @fluidinference]

Huge thanks to NVIDIA and all the launch partners!

[Fluid Inference @fluidinference]

NVIDIA's Nemotron 3.5 ASR Streaming Multilingual is now available through FluidAudio optimized for Apple Silicon so apps can run ~40-language real-time ASR entirely on device, no cloud required.

Apps shipping with it today include
@SpokenlyApp, @ALTIC_DEV, @SnaplyAI, and others.

FluidAudio:
https://t.co/VWaAPfLRh5

Original model:
https://t.co/87wRTlO5dm

@NVIDIAAIDev

[Fluid Inference @fluidinference]

https://t.co/LWslrdK4Yw

[Barathwaj Anandan @BarathAnandan7]

Today's a big day for Nemotron models.

Along with Ultra, we also shipped Nemotron Speech 3.5 that now supports 40 Languages and it's insanely Fast and Ultra Low latency!

I collaborated with @Alex_tra_memory, @fluidinference and @ALTIC_DEV to port the model to coreML to make bring the latest Nemotron model to any macbook using FluidVoice!

Give it a try and lmk what you think!

Link below ⬇️

[Fluid Inference @fluidinference]

https://t.co/Snc8Sg8XqZ

[Giacomo Venier @giacomovenier]

Snaply now supports NVIDIA Nemotron 3.5 ASR Multilingual via @FluidInference — 40 language-locales,
on-device, no cloud, free to use.

@NVIDIAAIDev @NVIDIAAI
#NemotronSpeech #VoiceAl

[Fluid Inference @fluidinference]

https://t.co/EksdOv5bix

[Spokenly @SpokenlyApp]

Spokenly now supports NVIDIA Nemotron 3.5 ASR Streaming Multilingual via @fluidinference — 40 locales, on-device, free, no subscription. Privacy-first dictation, now global.

App: https://t.co/l3j1rxlTMA
Model: https://t.co/FVfly8ZW8a
@NVIDIAAIDev #VoiceAI

[Fluid Inference @fluidinference]

https://t.co/dStiOjpTVP

[Audivize @audivizelabs]

Audivize now supports NVIDIA Nemotron 3.5 ASR Multilingual via @fluidinference, adding support for 40 language-locales all on-device.

Demo: https://t.co/RwWiEsPBe6

Model: https://t.co/aBzlrWGWkO

@NVIDIAAIDev @NVIDIAAI
#NemotronSpeech #VoiceAl

[Spokenly @SpokenlyApp]

Spokenly now supports NVIDIA Nemotron 3.5 ASR Streaming Multilingual via @fluidinference — 40 locales, on-device, free, no subscription. Privacy-first dictation, now global.

App: https://t.co/l3j1rxlTMA
Model: https://t.co/FVfly8ZW8a
@NVIDIAAIDev #VoiceAI

[Sachin Desai @sach1n]

Nemotron ASR Multilingual running on an iPhone 17 Pro in CoreML.

Many thanks to @fluidinference for the CoreML model and to @NVIDIAAI @NVIDIAAIDev for the model itself.

[ALTIC @ALTIC_DEV]

FluidVoice 1.5.15 now supports @NVIDIAAI Nemotron 3.5 ASR Multilingual collaborating with @fluidinference - 40 language-locales, free forever, fully on-device, and ultra fast!
👉Download here —> https://t.co/lprygBMhxg

@NVIDIAAIDev @NVIDIAAI #NemotronSpeech #VoiceAI

[Giacomo Venier @giacomovenier]

Snaply now supports NVIDIA Nemotron 3.5 ASR Multilingual via @FluidInference — 40 language-locales,
on-device, no cloud, free to use.

@NVIDIAAIDev @NVIDIAAI
#NemotronSpeech #VoiceAl

[Barathwaj Anandan @BarathAnandan7]

Today's a big day for Nemotron models.

Along with Ultra, we also shipped Nemotron Speech 3.5 that now supports 40 Languages and it's insanely Fast and Ultra Low latency!

I collaborated with @Alex_tra_memory, @fluidinference and @ALTIC_DEV to port the model to coreML to make bring the latest Nemotron model to any macbook using FluidVoice!

Give it a try and lmk what you think!

Link below ⬇️

[Sachin Desai @sach1n]

Supertonic3 running on an iPhone 17 Pro using ANE on CoreML. It’s blazing fast with low RAM consumption and background capable. 2 mins worth of audio generated in 3 secs.

Many thanks to @fluidinference for the port.

[Edd Mann @edd_mann]

rewrote VoiceScribe to use tca/swiftui, now focusing soley on local transcription/llm cleanup.

it now provides local whisper and parakeet (thanks to @fluidinference, coreml) transcription, coupled with optional local llm cleanup (mlx).

there are a lot of wrappers around these great transcription models, but i wanted to learn how to package and distribute local model inference for this use-case myself. it's been a lot of fun.

https://t.co/rqr5CRzX0L
https://t.co/azbE0KNZ3E

[Kris @B1R433]

Built a YouTube transcriber skill for Claude Code. Paste a URL, get a local transcript. Playlists, auto-chunking for long videos. Also downloads full video with --keep-video.

Powered by @FluidInference — install together with the fluidaudio-skill:
https://t.co/ilHFPmWjuK

[Fluid Inference @fluidinference]

🫡

[Kay Singh 📈🐦 @singhkays]

@brian_lovin Surprisingly easy using @fluidinference's libraries that leverage CoreML converted models like Nvidia Parakeet on Mac OS.

[Fluid Inference @fluidinference]

beautiful

[Alex @Alex_tra_memory]

FluidAudio now has a Mintlify docs site to help developers integrate local ASR, diarization, and TTS.

Big thanks to @mintlify's OSS program for giving open source projects free access to premium features.

https://t.co/WyiEGYesS9

[Alex @Alex_tra_memory]

we now support kyutai-lab's pocket tts in FluidAudio. PocketTTS is a streaming TTS that handles long text with seamless chunk transitions and is a more permissive model for commercial usages .

Get started here:
https://t.co/JK8nROUa60

credits to @sach1n for helping us test this & the video demo

[Alex @Alex_tra_memory]

i just finally got qwen-asr converted to cormel. what was surprisingly was that it uses a encoder -> embedder -> llm transcription. the architecture is quite alien from traditional nvidia transformer transducer pipelines.

this is something i am unfamiliar with but it does mean claude code is able to better grasp the LLM architecture given it still follows a standard LLM template. vs requiring alot more guidance for typical audio models.

i have linked the PR if anyone wants to take a look

https://t.co/iXMQ7cYwNA

[Sachin Desai @sach1n]

@Alex_tra_memory And here it is, @kyutai_labs PocketTTS on mobile.