Speech Swift is live · free plan; paid plans on request · last verified 25 Oct 2026 · viability monitor
Speech Swift
On-device speech SDK for real-time ASR, voice cloning, and full-duplex voice agents that never touch the cloud
The deepest open-source on-device speech catalogue on the market, and running VoiceChat 11B with real MCP tool calls at RTF 0.92 on an M5 Pro is the kind of thing you benchmark rather than trust a homepage for. What you're buying is an SDK, not a service: expect to spend engineering time picking models, sizing memory, and tracking releases. Check per-platform coverage first, since Linux and Android lag Apple Silicon.
Verdict generatedVerified 5d ago · liveness 68/100 · cite: rightaichoice.com/tools/speech-swift
- Teams building on-device voice agents where audio legally or contractually cannot leave the device
- Mobile engineers shipping streaming dictation or live captions under a tight memory budget (297 MB ASR on iPhone 16 Pro)
- Podcast, audiobook, and dubbing workflows that need cloned voices without uploading source audio
- Researchers benchmarking or self-hosting speech models across Apple Silicon, Android, and embedded Linux
- Buyers who want a no-code transcription or voice-generation product with a web dashboard
- Teams that need cloud-scale deployment without running or managing their own inference hardware
- Projects without engineering capacity to select models, size memory, and track frequent releases
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Skip Speech Swift if you want a hosted speech API with per-minute billing and someone else running the inference — this is an Apache 2.0 SDK you install, tune, and operate yourself.
Model weights download on first use and cache to ~/Library/Caches/qwen3-speech/, so a first request can stall 30 s to 2 min while a multi-gigabyte model lands.
The Apache 2.0 SDK is the entry point and costs nothing to adopt, which puts it below per-minute hosted speech APIs on pure software spend — but you pay in inference hardware and engineering time instead. It fits funded startups and established engineering teams with mobile or desktop deployment targets; a solo builder without hardware or ML experience will get to production faster on a managed API.
In short
Speech Swift — On-device speech SDK for real-time ASR, voice cloning, and full-duplex voice agents that never touch the cloud. Best for Teams building on-device voice agents where audio legally or contractually cannot leave the device, Mobile engineers shipping streaming dictation or live captions under a tight memory budget (297 MB ASR on iPhone 16 Pro), Podcast, audiobook, and dubbing workflows that need cloned voices without uploading source audio. Free to start; it also has paid plans whose price we could not confirm — see the pricing table.
What is Speech Swift?
Speech Swift — On-device speech SDK for real-time ASR, voice cloning, and full-duplex voice agents that never touch the cloud. Best for Teams building on-device voice agents where audio legally or contractually cannot leave the device, Mobile engineers shipping streaming dictation or live captions under a tight memory budget (297 MB ASR on iPhone 16 Pro), Podcast, audiobook, and dubbing workflows that need cloned voices without uploading source audio. Free to start; it also has paid plans whose price we could not confirm — see the pricing table.
Speech Swift is Soniqo's Apache 2.0 SDK for speech features that run entirely on-device, across Apple Silicon, Android, Windows, and embedded Linux. Audio never leaves the machine, there are no per-minute API bills, and thirty-plus models install behind one command (Homebrew on Apple, Gradle on Android). The component catalogue splits into speech-to-text, text-to-speech, audio analysis, and a speech-to-speech layer. On transcription you can pick Qwen3-ASR (52 languages), Omnilingual ASR (1,672 languages), CoreML Whisper large-v3 turbo, Parakeet TDT, Cohere Transcribe 2B, or MOSS Transcribe Diarize with 128K offline context. Diarization comes from Nemotron 3, Pyannote Community-1, and Sortformer, with Silero VAD and Smart Turn v3.2 ending turns at about 3.5 ms per pause. Synthesis covers zero-shot cloning (IndexTTS2, CosyVoice 3, Chatterbox Flash, Qwen3-TTS), voice design and cloning via VoxCPM2 at 48 kHz across 30 languages, and long-form output with VibeVoice for 90-minute podcasts. There is more than voice, too: DeepFilterNet3 enhancement, LocalVQE echo cancellation at 16 ms, Sidon dereverb, FlashSR super-resolution, and even Stable Audio 3 and MAGNeT MusicGen for music. A bundled Speech Server exposes every model as local REST and WebSocket endpoints, including an OpenAI Realtime API-compatible /v1/realtime socket. Soniqo's own consumer apps (Stenograf on the Mac App Store and Google Play) are the proof it ships. This is aimed at engineering teams — voice-agent builders, offline transcription pipelines, mobile engineers budgeting memory (Parakeet-EOU streams at 297 MB on an iPhone 16 Pro) — not at buyers who want a hosted per-minute API like Deepgram or AssemblyAI.
Key features
- Real-time and batch speech-to-text with Qwen3-ASR (52 languages, RTF 0.06, 4-/8-bit MLX)
- Omnilingual ASR across 1,672 languages in 300M–7B parameter variants (CoreML, MLX, LiteRT)
- CoreML Whisper large-v3 turbo at 1.40% WER with 6-second model load
- Streaming ASR with partial results and end-of-utterance detection (Parakeet EOU, 25 languages, ~232 MB)
- MOSS Transcribe Diarize 0.9B with 128K offline context and RTF 0.028
- Speaker diarization via Nemotron 3 (up to 8 speakers), Pyannote Community-1, and Sortformer
- On-device voice activity detection (Silero v6.2.1, Pyannote, FireRedVAD)
- End-of-turn detection with Smart Turn v3.2 at 3.5 ms per pause across 23 languages
- Wake-word and keyword spotting (KWS Zipformer at 26x real-time)
- Forced alignment with word-level timestamps at 80 ms precision
- Zero-shot voice cloning via IndexTTS2, CosyVoice 3, Chatterbox Flash, and Qwen3-TTS
- 48 kHz voice cloning and voice design (VoxCPM2, 30 languages); Kokoro with 54 voices
- Long-form speech synthesis for podcasts and audiobooks (VibeVoice 90-minute output, Magpie 357M)
- Full-duplex speech-to-speech on-device (PersonaPlex 7B, VoiceChat 11B asymmetric duplex, RTF 0.92–0.94 on M5 Pro)
- Local HTTP + WebSocket Speech Server with REST endpoints and OpenAI Realtime API-compatible /v1/realtime socket
Behind the verdict
Where Soniqo earns its keep is the constraint case. If audio contractually or legally cannot leave the device — clinical notes, legal discovery, in-car or robotics, anything under GDPR scrutiny — the alternative to Speech Swift is a cloud API plus a compliance review, and the SDK frequently wins on cost alone once you're past a few thousand minutes a month. The breadth is unusual. Diarization, VAD, end-of-turn detection, wake-word spotting (KWS Zipformer at 26x real-time), forced alignment at 80 ms, and even source separation and music generation all ship in one stack. Patching together Whisper, Pyannote, and a TTS library yourself is a weekend of glue code and a year of maintenance you now hand to someone else. Real-world caveats bite in three places. First, model shopping is on you: thirty-plus components with per-model quantization, memory footprints, and license terms (some TTS models are non-commercial), so somebody has to read the cards. Second, platform parity isn't guaranteed — the site says all run on Apple Silicon, most on Android and Linux, and the published benchmarks are Apple-heavy. Third, releases move fast, so pin versions and test before upgrading. The full-duplex voice-agent path is the most compelling and the least turnkey. VoiceChat 11B at 8.70 GB RSS is a desktop-class footprint; for phones you'll want the smaller Parakeet-EOU plus FunctionGemma command pipeline instead. We'd reach for Speech Swift when you have an engineer who owns speech. If you don't want that owner, pay Deepgram or AssemblyAI for minutes instead — that's a staffing decision, not a quality one.
Models under the hood
as of 2026-10-25
Limitations
- Speech Swift is a self-hosted SDK, not a hosted service: you install it (Homebrew on Apple platforms, Gradle on Android) and own inference, memory budgets, and upgrades.
- It runs on Apple Silicon, Android, Windows, and embedded Linux with no cloud APIs and no per-minute pricing, so data stays on the device.
- On-device memory varies: Soniqo measured a full voice-agent loop at ~1.2 GB on iPhone, ~1.5 GB on Galaxy S23, and the desktop loop (including a Gemma 4 brain) under ~4 GB.
as of 2026-10-08
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Is Speech Swift still active?
Speech Swift is live · free plan; paid plans on request · last verified 25 Oct 2026 · viability monitor.
Viability score
How well maintained and how widely used is Speech Swift? Built from what the vendor actually publishes (docs, changelog, tutorials, integrations, pricing), whether the site is live, and how much real users discuss it. How we calculate this
Last calculated: October 2026
How we score →What's new in Speech Swift
Checked 7 days agoAcross the latest 1 update: 1 news mention.
What do users say about Speech Swift?
What people actually say about Speech Swift — is it worth it?
We ran a structured research pass across product reviews, community discussions, and post-purchase forum threads to surface the patterns vendors won't publish themselves. Below: the recurring strengths, the hidden costs people mention most, and the cohort that consistently regrets adopting this tool.
Researched34 mentions across 5 sources (Hacker News, YouTube, Product Hunt, GitHub, Lemmy) · researched Sep 14, 2026.
Weighted by the 68 posts each of 5 sources contributed.
- +Fully on-device inference means no cloud calls, no per-minute billing, and no audio leaving hardware
- +Apache 2.0 license is genuinely permissive for commercial use, which most local speech stacks are not
- +Benchmarks are specific — RTF 0.06 ASR, 32× realtime Parakeet on Apple Neural Engine
- +Breadth is unusual: ASR, TTS, diarization, VAD, wake-word, cloning, and full-duplex in one SDK
- +Native Swift async/await APIs make Apple integration cleaner than wrapping Python tools
- −Quality claims are unverified by any independent benchmark or third-party test in the community data
- −Community discussion is dominated by maintainer self-promotion rather than organic user reports
- −Direct question about voice-cloning quality vs. cloud APIs remains unanswered on Product Hunt
- −Android and Windows support is thinner than the Apple Silicon path, with fewer examples
- −Managing 30+ models and picking the right one is real integration work, not a drop-in API
- • Engineering time to integrate 30+ models and select the right one per task
- • Hardware cost — an M-series Mac or recent iPhone is effectively required for the best performance
- • Commercial Speech Server pricing is unpublished, so enterprise cost planning is guesswork
How we verified this
Every listed fact about Speech Swift— pricing, features, links, status — is re-read from the vendor's own pages by our verification pipeline and each change is logged with a date; the last pass ran on 25 Oct 2026. Pages mix model-assisted synthesis with human review; see how we verify.
Verification history
We have re-verified Speech Swift 10 times since . Each pass re-reads the vendor's own pages and re-checks every listed field against that evidence; passes where nothing had changed are marked as such.
- — changed pricing tiers, who it suits, our verdict, who should skip it, description, features
- — changed our verdict, summary, features, pricing tiers, who it suits, who should skip it, description
- — changed pricing page, limitations, models
- — changed features, description, pricing tiers, who should skip it, summary, our verdict, who it suits
- — changed pricing page
- — changed switching in, who it suits, use cases, description, summary, our verdict, who should skip it, features, setup time, pricing fit, hidden costs, limitations, switching out, models
Showing the 6 most recent of 10 verification passes.
Free to cite with attribution — this page re-verifies continuously.
How much does Speech Swift cost in 2026?
Speech Swift: Free to start; it also has paid plans whose price we could not confirm — see the pricing table. Pricing last verified 25 Oct 2026.
Plans compared
Every published Speech Swift tier, its price as the vendor publishes it, who it fits, and what it adds over the tier below. The 12-month cost projection follows.
| Plan | Price | Billing | Who it's for |
|---|---|---|---|
| Open-Source SDK | Free | — | Engineering teams shipping on-device speech on Apple Silicon, Android, Windows, or embedded Linux who can own the inference pipelineAdds: Starting tier: Apache 2.0 licence with 30+ models, Swift/CLI APIs, and Homebrew or Gradle installs at no cost |
| Soniqo Speech Server / Cloud | Contact | quote | — |
12-month cost
Project the real annual outlay, including the implied monthly cost when only an annual tier is published.
Vendor list price only. Add-on usage, seat overages, and contract minimums are surfaced under Hidden costs & gotchas.
Where the pricing makes sense
The company stage and team size where Speech Swift's pricing actually pencils out — and where peers do it cheaper.
The Apache 2.0 SDK is the entry point and costs nothing to adopt, which puts it below per-minute hosted speech APIs on pure software spend — but you pay in inference hardware and engineering time instead. It fits funded startups and established engineering teams with mobile or desktop deployment targets; a solo builder without hardware or ML experience will get to production faster on a managed API.
Has Speech Swift's pricing changed?
No plan price for Speech Swift has moved since we began logging in Aug 2026; the pricing page is re-read on every verification pass.
Who should pick Speech Swift?
Pick Speech Swift if you are Teams building on-device voice agents where audio legally or contractually cannot leave the device, Mobile engineers shipping streaming dictation or live captions under a tight memory budget (297 MB ASR on iPhone 16 Pro), Podcast, audiobook, and dubbing workflows that need cloned voices without uploading source audio, Researchers benchmarking or self-hosting speech models across Apple Silicon, Android, and embedded Linux.
Look elsewhere if you are Buyers who want a no-code transcription or voice-generation product with a web dashboard, Teams that need cloud-scale deployment without running or managing their own inference hardware, Projects without engineering capacity to select models, size memory, and track frequent releases, Use cases requiring identical model coverage and latency across iOS, Android, and Linux from day one.
Skip it if Skip Speech Swift if you want a hosted speech API with per-minute billing and someone else running the inference — this is an Apache 2.0 SDK you install, tune, and operate yourself.
GeneratedReal-world workflow fit
Concrete scenarios for the personas Speech Swift actually fits — and what changes day-one when you adopt it.
Install via Homebrew, wire the Swift API to a VAD → Parakeet EOU streaming STT → Qwen3.5 Chat → Pocket TTS loop, and cap the pipeline inside the ~1.2 GB iPhone budget Soniqo published.
Outcome: A voice assistant that answers and calls tools without sending a single audio byte off the handset.
Clone a host voice from a short reference sample with CosyVoice 3 or Chatterbox Flash, then generate a 90-minute episode through VibeVoice and review the WER/similarity numbers from Soniqo's five-language cloning benchmark.
Outcome: Finished narration in the host's voice, produced locally with the source audio never uploaded.
Run `speech-server --port 8080`, point an existing OpenAI Realtime SDK client at ws://127.0.0.1:8080/v1/realtime, and enable server_vad turn detection so Silero VAD commits each speech turn automatically.
Outcome: The same realtime client code now runs against local models with no per-minute fees.
Use cases
- Transcribe live meetings or dictation with streaming ASR and named-speaker diarization, entirely offline.
- Clone a voice from a short reference sample to generate custom synthetic speech for content.
- Build a voice-controlled assistant with wake-word detection and full-duplex speech-to-speech.
- Process batch audio archives with multilingual transcription spanning up to 1,672 languages.
- Create long-form audiobooks or podcasts with 90-minute VibeVoice synthesis and voice cloning.
- Deploy a conversational voice agent on Mac or Android that handles interruptions and calls tools via MCP.
- Run a local HTTP/WebSocket speech server that existing OpenAI Realtime clients can point at.
- Generate music or audio effects locally for games and content with Stable Audio 3 and MAGNeT.
Setup time & first value
How long it actually takes to get something useful out of Speech Swift — broken out by persona, not the marketing-page minute.
Developers with an Apple toolchain: `brew install speech` and a first transcription is typically minutes away, though each new model adds a 30 s–2 min download-and-load on first use. Android engineers should budget longer — Gradle install plus LiteRT/ONNX model setup and per-model verification. Backend teams standing up speech-server get a health check immediately but 30–60 s of boot if they
Switching to or from Speech Swift
How to bring data in from common predecessors and how to get it back out — written for the switcher, not the buyer.
- →From a hosted speech API (AssemblyAI, Deepgram): re-point your client at local speech-server endpoints or the /v1/realtime socket and replace per-minute billing with your own inference hardware.
- →From Apple's Speech framework: swap basic dictation for Qwen3-ASR or Parakeet TDT to add diarization, cloning, and full-duplex conversation the system framework doesn't cover.
- →From a cloud TTS vendor: replace the API call with CosyVoice 3 or VoxCPM2 cloning driven from a short reference sample stored on-device.
- →From scattered open-source scripts: consolidate Whisper, Silero, and pyannote tooling under one CLI, Swift API, and Homebrew or Gradle install path.
- ↗To a managed API (AssemblyAI, Deepgram): when you'd rather pay per minute than own inference hardware and model updates.
- ↗To a no-code SaaS transcription product: when you need a web dashboard and don't want to ship an SDK.
- ↗To Apple's Speech framework: when your needs are basic dictation and you'd prefer the smallest possible integration surface.
Resources & guides
Tutorials & Learning
YouTube returned 6 videos for “Speech Swift”, and we withheld 6: 6 did not mention Speech Swift. We are showing none, because we could not prove any of them are about Speech Swift.
Official links
What are the best Speech Swift alternatives?
The closest alternatives to Speech Swift we list are ElevenLabs, Smallest.ai and Fish Audio. Ranked by direct product-type match, not category overlap.
| Alternative | Pricing | Starts at | Last verified |
|---|---|---|---|
| ElevenLabs | Freemium | Pricing not published | — |
| Smallest.ai | Freemium | Pricing not published | — |
| Fish Audio | Freemium | Pricing not published | — |
Alternatives to Speech Swift
View allElevenLabs
AI audio platform: text to speech, voice cloning, transcription and phone/chat voice agents on one shared credit pool.
Smallest.ai
Smallest.ai delivers realtime text-to-speech, speech-to-text, speech-to-speech and voice agents on one developer API.
Fish Audio
Fish Audio delivers expressive AI text-to-speech and 15-second voice cloning across 30+ languages with emotion tags.
Tools that pair well with Speech Swift
Common stack mates teams adopt alongside Speech Swift, with the specific reason each pairing earns its keep.
ElevenLabs
AI audio platform: text to speech, voice cloning, transcription and phone/chat voice agents on one shared credit pool.
Smallest.ai
Smallest.ai delivers realtime text-to-speech, speech-to-text, speech-to-speech and voice agents on one developer API.
Fish Audio
Fish Audio delivers expressive AI text-to-speech and 15-second voice cloning across 30+ languages with emotion tags.
Speech Swift vs its closest rival
Speech Swift's closest head-to-head is with Spider Cloud — Choose Speech Swift if you need a privacy-focused, on-device speech AI toolkit for Apple Silicon with offline ASR, TTS, and voice cloning. Opt for Spider Cloud if you require a high-performance, pay-as-you-go web crawling and scraping API to feed real-time data into AI agents or RAG pipelines. They serve completely different primary needs, so pick based on whether your bottleneck is speech processing or web data extraction. Verdict generated
Head-to-head comparisons
Speech Swift vs Spider Cloud
Choose Speech Swift if you need a privacy-focused, on-device speech AI toolkit for Apple Silicon with offline ASR, TTS, and voice cloning. Opt for Spider Cloud if you require a high-performance, pay-as-you-go web crawling and scraping API to feed real-time data into AI agents or RAG pipelines. They serve completely different primary needs, so pick based on whether your bottleneck is speech processing or web data extraction.
GeneratedSpeech Swift vs Voyage Ai
Choose Voyage AI if your primary need is high-accuracy retrieval for enterprise RAG pipelines, especially with domain-specific embeddings for finance or legal and long-context support up to 32K tokens. Choose Speech Swift if you need on-device, privacy-preserving speech AI (ASR, TTS, voice cloning) with no cloud dependency, and you're comfortable with a developer-focused toolkit. These tools serve fundamentally different purposes and are not direct competitors.
GeneratedSpeech Swift vs Temporal Ai
For building on-device speech AI with full privacy, Speech Swift is the pick: it's open-source, runs locally on Apple Silicon, and supports everything from ASR to voice cloning without cloud reliance. For orchestrating reliable AI agents or multi-step microservices that must survive failures, Temporal is the standard — it's trusted by OpenAI and Replit, offers multiple SDKs, and just added Serverless Workers. Choose based on your primary job: speech processing vs. workflow resilience. If you need both, they can complement each other.
GeneratedFrequently asked questions
Best-of guides
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