ElevenLabs Conversational AI vs Kyutai Moshi

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

	ElevenLabs Conversational AI Audio	Kyutai Moshi Audio
Tagline	Production-grade voice agent platform layering ElevenLabs TTS, ASR, and LLM orchestration into a single deployable stack.	Open-source, full-duplex speech-to-speech foundation model with sub-200ms latency
Category	Audio	Audio
Pricing	Paid· Free: $0 · Starter: $6 · Creator: $11 · Pro: $99 · Scale: $299	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).
Model	ElevenLabs Scribe (ASR) + pluggable LLM + ElevenLabs TTS	Moshi (7B-class speech-text foundation model) + Mimi neural audio codec, in-house by Kyutai
Editorial score	8.1 / 10	—
Use cases	voice-agentsivr-replacementcustomer-supportphone-automationmultilingual-chatbots	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
Pros	Best-in-class voice quality inherited from ElevenLabs TTS Sub-second latency good enough for real phone calls 70+ languages with live detection and switching SOC 2, HIPAA, and GDPR compliance baked in SDKs plus telephony integrations (Twilio, Genesys, SIP)	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
Cons	Pricing opaque on the product page; sales-led for real deployments Closed source with no self-hosted option Locked into ElevenLabs' voice and ASR stack	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
Website	elevenlabs.io	kyutai.org

Pick ElevenLabs Conversational AI if

✅ Best-in-class voice quality inherited from ElevenLabs TTS
✅ Sub-second latency good enough for real phone calls
✅ 70+ languages with live detection and switching
✅ SOC 2, HIPAA, and GDPR compliance baked in

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

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