microsoft/VibeVoiceGitHub
calls FluidAudio “same tasks in a Swift/CoreML library for Apple platforms, not a Python drop-in”
Open-Source Frontier Voice AI
53.1kPythonactive
FluidInference/FluidAudio Alternatives
FluidAudio is queued for analysis. Crawling candidates and ranking them takes a few minutes. This page updates itself when the list exists — you can also come back later.
What is known so far comes from the other direction:
Listed as an alternative to
These projects were analysed and named FluidAudio among their alternatives. The relationship is not symmetric — how FluidAudio rates them is a separate judgement, made when FluidAudio is analysed in its own right.
NVIDIA-NeMo/SpeechGitHub
calls FluidAudio “choose when building Swift/CoreML Apple apps needing on-device speech models.”
A scalable generative AI framework built for researchers and developers working on Large Language Models, Multimodal, and Speech AI (Automatic Speech Recognition and Text-to-Speech)
18.3kPythonactive
alphacep/vosk-apiGitHub
calls FluidAudio “Apple-only CoreML speech models for native iOS/macOS apps.”
Offline speech recognition API for Android, iOS, Raspberry Pi and servers with Python, Java, C# and Node
15.1kJupyter Notebookactive
k2-fsa/sherpa-onnxGitHub
calls FluidAudio “Use when you are building an Apple-only app and want native CoreML-accelerated speech models instead of ONNX cross-platform.”
Speech-to-text, text-to-speech, speaker diarization, speech enhancement, source separation, and VAD using next-gen Kaldi with onnxruntime without Internet connection. Support embedded systems, Android, iOS, HarmonyOS, Raspberry Pi, RISC-V, RK NPU, Axera NPU, Ascend NPU, x86_64 servers, websocket server/client, support 12 programming languages
14.5kC++active
speechbrain/speechbrainGitHub
calls FluidAudio “Choose when you're building a Swift/CoreML Apple app and need on-device audio models.”
A PyTorch-based Speech Toolkit
11.8kPythonactive
moonshine-ai/moonshineGitHub
calls FluidAudio “choose when you're building Apple-only Swift/CoreML apps and want native audio models without a cross-platform dependency.”
Very low latency speech to text, intent recognition, and text to speech, for building voice agents and interfaces
10.9kC++active
QuentinFuxa/WhisperLiveKitGitHub
calls FluidAudio “when building Apple apps and want CoreML-based on-device STT/diarization in Swift”
Real-time, local speech-to-text with streaming ASR, speaker diarization, translation, and OpenAI/Deepgram-compatible APIs.
10.9kPythonactive
KoljaB/RealtimeSTTGitHub
calls FluidAudio “Choose for Swift/CoreML Apple apps where a Python library cannot be embedded; it is platform-specific to Apple.”
A robust, efficient, low-latency speech-to-text library with advanced voice activity detection, wake word activation and instant transcription.
10.1kPythonactive
modelscope/FunASRGitHub
calls FluidAudio “choose for Apple-native speech models (ASR/TTS/VAD) via CoreML in Swift.”
Open-source speech recognition toolkit for training, inference, streaming ASR, VAD, punctuation, speaker diarization pipelines, and OpenAI-compatible/MCP serving.
20.0kPythonactive
espnet/espnetGitHub
calls FluidAudio “Choose when building Apple apps that require CoreML-based speech models, as a platform-specific wrapper.”
End-to-End Speech Processing Toolkit
9.9kPythonactive