Grain vs Kyutai Moshi

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

	Grain Audio	Kyutai Moshi Audio
Tagline	AI meeting notes, coaching, and an MCP feed for your agents	Open-source, full-duplex speech-to-speech foundation model with sub-200ms latency
Category	Audio	Audio
Pricing	Freemium· Free (45-min meeting cap, 90-day history) / Starter ~$15 per user/mo (unlimited meetings, advanced AI) / Business & Enterprise tiers with CRM sync and admin controls	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	Claude, ChatGPT	Moshi (7B-class speech-text foundation model) + Mimi neural audio codec, in-house by Kyutai
Editorial score	8.3 / 10	—
Use cases	AI meeting notes and summariesSales call transcription and coachingCustomer discovery call analysisCRM auto-updates from meetingsHighlight clip sharing to Slack/NotionCross-meeting AI Q&A searchMCP feed into Claude or ChatGPT agentsProduct research interview libraryDeal review and pipeline insightsCustomer success handoff documentation	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	Bot-less desktop capture is much less intrusive than a Zoom bot on every call MCP server + API make it one of the easier notetakers to plug into Claude/ChatGPT/custom agents Deal views and CRM sync (HubSpot, Salesforce) cover most GTM workflows without Gong-tier pricing Highlight clips and shareable moments make handoffs between sales, CS, and product genuinely fast 130+ language transcription and cross-meeting AI search work well on real, messy call libraries Perpetual free tier is generous enough to actually evaluate the product on real meetings	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	Conversation intelligence and coaching depth still trail Gong and Chorus for large enterprise teams Advanced AI, CRM sync, and coaching features are gated behind paid tiers — free plan is limited to 45-minute meetings Does not disclose which underlying LLM powers its own summaries, which matters for compliance reviews Video/scorecard analytics are lighter than dedicated revenue intelligence platforms MCP + agent integrations are new and the ecosystem around them is still maturing	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	grain.com	kyutai.org

Pick Grain if

✅ Bot-less desktop capture is much less intrusive than a Zoom bot on every call
✅ MCP server + API make it one of the easier notetakers to plug into Claude/ChatGPT/custom agents
✅ Deal views and CRM sync (HubSpot, Salesforce) cover most GTM workflows without Gong-tier pricing
✅ Highlight clips and shareable moments make handoffs between sales, CS, and product genuinely fast

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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