MisoTTS
MisoTTS is an 8B-parameter text-to-speech model from Miso Labs for expressive speech and dialogue generation. The official weights and local inference code are on Hugging Face, and the current model card links a web demo, but it does not document a stable hosted API model ID, price, or limit set.
MisoTTS is page-worthy because it is a fresh voice-model release with primary-source technical detail, open weights, and early community attention around expressive speech generation. It also gives GetLLMs a current speech-model explainer without pretending the API/catalog fields are stable enough for a `/models` directory record.
Miso Labs announced MisoTTS on June 3, 2026 as an 8B-parameter model for emotive speech and dialogue generation. The official blog describes a 7.7B backbone plus 300M decoder, residual vector quantization with 32 audio codebooks, text and optional audio-context conditioning, and current half-duplex limitations. The current Hugging Face model card confirms the MisoLabs/MisoTTS repository, local inference code, model summary, license field, and a web-demo link, but it does not publish a stable hosted API model ID, price, or limit set. Hacker News is used only as freshness and demand evidence.
- Track Miso Labs speech-model release facts and availability.
- Compare expressive TTS models that use text plus audio context.
- Understand RVQ-style audio tokenization in a reader-friendly way.
- Decide whether to wait for hosted API access before production evaluation.
The official release describes MisoTTS as an 8B-parameter speech model for expressive speech and dialogue generation. It generates from text and optional audio context, uses residual vector quantization, and is built around a 7.7B-parameter backbone with a 300M-parameter decoder.
- Task: text-to-speech and expressive speech generation.
- Architecture: a large temporal backbone plus a smaller depth decoder for audio codebooks.
- Availability: official weights, local inference code, and a linked web demo are live; stable hosted API fields are not published.
The Hugging Face card is useful for model identity, task, setup, and architecture, but it also says the model is not deployed by an Inference Provider. Until a stable public API, provider ID, pricing, limits, and hosted availability are verified, this should remain an entity explainer rather than a structured `/models` catalog entry.
Miso Labs says the current model handles individual turns and half-duplex audio, but does not yet solve turn-taking or full-duplex conversation. Treat quality and expressiveness claims as vendor-provided until independent evaluations and provider listings mature.
OpenMOSS speech-generation family with flagship, local, realtime, dialogue, voice-design, and Nano variants.
Recent model entity that also separates launch facts from directory-grade API metadata.
Recent Microsoft model entity with deferred `/models` catalog status.
MisoTTS FAQ
Common questions about MisoTTS.
What is MisoTTS?+
MisoTTS is an 8B-parameter text-to-speech model from Miso Labs for expressive speech and dialogue generation. It can generate speech from text and optional audio context, with open weights available on Hugging Face.
Can I use MisoTTS through a hosted API?+
No stable hosted API contract is documented in the current official model card. You can use the official weights and local inference code or try the linked web demo, but production integration should wait for a verified provider model ID, pricing, limits, and availability terms.
Why does MisoTTS use residual vector quantization?+
Miso Labs uses residual vector quantization to represent audio with multiple codebook indices instead of one very large flat vocabulary. The goal is to cover more speech variation while keeping the model architecture practical.