A detailed analysis of TTS costs, concurrency, and performance for production voice agents.
Voice agent developers face significant challenges in managing the costs of text-to-speech (TTS) models, which represent the most expensive component of the typical cascaded architecture used in production: speech-to-text, large language model, and text-to-speech. A recent analysis highlights the complexities of comparing TTS costs due to varying character-to-minute conversion rates, hidden fees for concurrency, and differences in performance metrics.
According to the analysis, only a small number of TTS providers meet the naturalness and responsiveness requirements for production-scale voice agents. These include AssemblyAI, ElevenLabs, Cartesia, Rime, and Fish. Each provider offers different pricing structures and performance characteristics, making direct comparisons challenging.
To standardize cost comparisons, the analysis uses a conversion factor of 600 characters per minute, derived from extensive production data. The normalized per-minute costs for each provider are as follows:
Concurrency limitations and hidden fees are a significant pain point for developers. Most TTS providers require annual contracts to unlock production-scale concurrency, with an average spend commitment of $10 per month for each concurrent voice agent call. This can result in substantial upfront costs for scaling new applications, as unused commitments are non-refundable.
In contrast, AssemblyAI offers unlimited concurrency without requiring spend commitments, allowing developers to scale their applications without hitting concurrency ceilings or negotiating additional contracts.
009 per minute), and unlimited concurrency. These features make it a compelling choice for developers seeking to optimize both cost and performance in production environments.
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