Models are constantly being trained and finetuned based on user and customer feedback. Please check back often as we push changes frequently.

There are currently 3 models that Rime has in production, arcana, mistv2 and mist.

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Arcana

Arcana, released April 2025, is Rime’s most expressive and lifelike TTS model to date. It pushes the boundary of naturalness and emotional depth in synthesized speech.

  • Highly expressive, natural-sounding speech with emotional nuance
  • Fine-grained control over prosody, pacing, and tone
  • Supports a wide range of vocal demographics, including different ages, accents, and cultural backgrounds
  • Enhanced realism for dynamic, conversational, and character-driven use cases
  • Available via modelId: arcana through Rime’s API endpoints

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Mist

Mistv2, released February 2025 has the following features:

  • Multi-lingual English + Spanish, plus more languages coming soon
  • More realistic speech with natural and contextual nuances
  • Advanced pronunciation control
  • Ultra-fast on-prem latency of ~70ms, perfect for real-time applications
  • More accents, demographics, and speaking styles

Mist is Rime’s next generation TTS engine, released April 2023, capable of synthesizing conversational speech. Using the modelId parameter for Rime’s TTS endpoints, specifying mistv2 or mist, will allow you to synthesize speech using this newer family of models. As of February 2025, the default value for modelId when unspecified is mist.

Model v1 was released in April 2022 and has been deprecated.

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Additional Controls

Arcana also supports several additional controls due to its LLM backbone. We recommend leaving these on the default values.

  • temperature: Controls the randomness of the generated speech.
    • Low (0): Produces more predictable and focused speech.
    • High (1+): Introduces variability in prosody and expression, potentially leading to more dynamic speech patterns.
  • repetition_penalty: Discourages the model from repeating the same sounds.
    • Low (<1): May result in repetitive speech patterns.
    • High (>1): Encourages variation, leading to more natural-sounding speech and realistic laughter.
  • top_p: Determines the diversity of choices by limiting the selection to a subset of probable sounds.
    • Low (0): Restricts the model to the most probable sounds, resulting in more monotonic speech.
    • High (1): Allows for a broader range of sound choices, enhancing the naturalness and variability of speech.

See the Arcana API reference pages for more details.