Kyutai Moshi vs Soundraw

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

	Kyutai Moshi Audio	Soundraw Audio
Tagline	Open-source, full-duplex speech-to-speech foundation model with sub-200ms latency	AI music generator that spits out royalty-free, customizable tracks by genre and mood.
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· Creator: €5.83/mo · Artist Starter: €10.75/mo · Artist Pro: €12.42/mo · Artist Unlimited: €17.42/mo · Enterprise: Ask
Model	Moshi (7B-class speech-text foundation model) + Mimi neural audio codec, in-house by Kyutai	Proprietary in-house model
Editorial score	—	8.2 / 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	background musicvideo soundtrackspodcast introsstem exportroyalty-free beats
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	Trained on in-house music, avoiding the copyright cloud over scrape-trained rivals Cheap entry tier ($5.99/mo) with unlimited MP3 downloads Bar-level editing and stem export for real DAW work Perpetual commercial license with creator royalty retention Public API for embedding generation in other apps
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	Instrumental only; no vocals or lyric generation Output is polished but generic, more library music than artistic Stems and WAV gated behind higher tiers Closed source, proprietary model with no model details
Website	kyutai.org	soundraw.io

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 Soundraw if

✅ Trained on in-house music, avoiding the copyright cloud over scrape-trained rivals
✅ Cheap entry tier ($5.99/mo) with unlimited MP3 downloads
✅ Bar-level editing and stem export for real DAW work
✅ Perpetual commercial license with creator royalty retention

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