Kyutai Moshi vs Wispr Flow

A side-by-side look at pricing, capabilities, pros, cons, and our editorial scores.

	Kyutai Moshi Audio	Wispr Flow Audio
Tagline	Open-source, full-duplex speech-to-speech foundation model with sub-200ms latency	System-wide voice-to-text dictation that auto-edits filler words and learns your jargon.
Category	Audio	Audio
Pricing	Free· Free and open source. Models under CC-BY 4.0, code under MIT (Python) / Apache 2.0 (Rust). Self-hosted only — you pay your own compute (24GB+ GPU for PyTorch, or Apple Silicon via MLX).	Freemium· Pro Monthly Plan: $15.00 · Pro Annual Plan: null · Monthly Student Plan: $7.49 · Pro Weekly Plan: $4.49 · Annual Student Plan: null
Model	Moshi (7B-class speech-text foundation model) + Mimi neural audio codec, in-house by Kyutai	—
Editorial score	—	8.0 / 10
Use cases	Real-time voice assistant prototypesResearch on full-duplex spoken dialogueOn-device voice interaction on Apple Silicon via MLXLow-latency conversational agents behind WebSocketNeural audio codec experimentation with MimiSelf-hosted voice interface for privacy-sensitive appsSpeech tokenizer for downstream audio LLM trainingInterruptible in-car or wearable voice UX	dictationvoice-to-textemail draftingcode commentsmultilingual transcription
Pros	Truly full-duplex — handles interruptions, overlap and back-channels rather than rigid turn-taking Sub-200ms practical latency on a single L4 GPU, well below third-party voice APIs Fully open weights (CC-BY 4.0) plus MIT/Apache code — self-host with no per-minute billing Ships with Mimi, a streaming neural audio codec that beats SpeechTokenizer and SemantiCodec Multiple inference backends: PyTorch for research, Rust/Candle for production, MLX for on-device Mac/iPhone Inner-monologue text prediction gives you a transcript alongside the audio stream for free	Auto-edits filler words and self-corrections in real time Works inside 50+ apps including IDEs, Slack, Gmail, ChatGPT Personal dictionary handles names, jargon and acronyms 100+ languages with auto-detection Cross-platform: Mac, Windows, iOS, Android with sync
Cons	English-only voices at launch — no multilingual support out of the box Knowledge and reasoning quality trail top text LLMs; it's a 7B-class model, not GPT-4o Voice Requires a 24GB+ GPU for the reference PyTorch build; on-device is only viable via MLX on Apple Silicon No hosted API or SaaS tier — you own the ops, scaling and safety filtering Only two fixed synthetic voices (Moshiko/Moshika); no voice cloning or speaker conditioning in the release	No public API for integration or automation Closed source; requires broad system-level mic permissions Pricing details are gated behind signup
Website	kyutai.org	wisprflow.ai

Pick Kyutai Moshi if

✅ Truly full-duplex — handles interruptions, overlap and back-channels rather than rigid turn-taking
✅ Sub-200ms practical latency on a single L4 GPU, well below third-party voice APIs
✅ Fully open weights (CC-BY 4.0) plus MIT/Apache code — self-host with no per-minute billing
✅ Ships with Mimi, a streaming neural audio codec that beats SpeechTokenizer and SemantiCodec

Pick Wispr Flow if

✅ Auto-edits filler words and self-corrections in real time
✅ Works inside 50+ apps including IDEs, Slack, Gmail, ChatGPT
✅ Personal dictionary handles names, jargon and acronyms
✅ 100+ languages with auto-detection

Compare a different pair →