Kyutai Moshi vs Retell AI

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

	Kyutai Moshi Audio	Retell AI Audio
Tagline	Open-source, full-duplex speech-to-speech foundation model with sub-200ms latency	Build, test and deploy production-grade AI voice agents for inbound and outbound calls.
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· Pay-as-you-go: $0.07-$0.31/minute · Enterprise: Custom Pricing
Model	Moshi (7B-class speech-text foundation model) + Mimi neural audio codec, in-house by Kyutai	LLM-agnostic (OpenAI, Anthropic, Google and others selectable per agent); proprietary turn-taking model and voice pipeline in-house
Editorial score	—	—
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	AI inbound call answeringOutbound lead qualificationAppointment scheduling and remindersCollections and payment dialers24/7 customer support triageIVR replacementHealthcare intake and follow-up callsInsurance claims first-notice-of-lossVoice-enabled RAG knowledge assistantsChat and SMS agents sharing a voice knowledge base
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	Sub-second end-to-end latency (~600 ms) with a purpose-built turn-taking model — conversations feel natural rather than walkie-talkie. Batteries-included telephony: bring Twilio/Vonage/Telnyx/Amazon Connect or use Retell-provisioned numbers with SIP trunking. Real function calling for booking, transfers, payments and CRM writes, with pre-built HubSpot, Salesforce, Cal.com, n8n, Zapier and Make integrations. Streaming RAG knowledge base with auto-sync, plus simulation testing and continuous QA — the operational glue most DIY voice stacks skip. Enterprise compliance out of the box: HIPAA, SOC 2 Type II, GDPR, PII removal and safety guardrails as toggleable add-ons. Genuinely transparent pay-as-you-go pricing with a $10 starter credit, so you can benchmark cost per call before committing.
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	Per-minute costs stack quickly once you enable QA ($0.10/min), knowledge base, denoising and premium LLMs — a 'cheap' agent can land near $0.30+/min. The specific LLMs are pluggable but Retell doesn't publish a default recommendation, so cost/quality tuning is on you. Not open source and there is no self-hosted option — regulated buyers who need on-prem inference are out of scope. Voice/telephony focus means it is overkill (and overpriced) for pure text chatbots you could run on a generic LLM API. True enterprise features (unlimited concurrency, custom compliance, dedicated support) require a sales conversation, not a self-serve upgrade.
Website	kyutai.org	www.retellai.com

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 Retell AI if

✅ Sub-second end-to-end latency (~600 ms) with a purpose-built turn-taking model — conversations feel natural rather than walkie-talkie.
✅ Batteries-included telephony: bring Twilio/Vonage/Telnyx/Amazon Connect or use Retell-provisioned numbers with SIP trunking.
✅ Real function calling for booking, transfers, payments and CRM writes, with pre-built HubSpot, Salesforce, Cal.com, n8n, Zapier and Make integrations.
✅ Streaming RAG knowledge base with auto-sync, plus simulation testing and continuous QA — the operational glue most DIY voice stacks skip.

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