The thesis is that TTS selection for voice agents is a multi-constraint engineering choice, not a single-score contest. The page reports 26 models and presents streaming latency, accuracy, naturalness, price, and stopping behavior as separate dimensions. Inworld TTS-2 Flash is listed at 45 ms streaming latency, 93.2% accuracy, and $15 per million characters; Gradium TTS is listed at 79.5% accuracy and is described as starting before the final word arrives on streamed text.
The mechanism is Conversational performance depends on when audio begins, whether spoken content is understood correctly, and whether output can stop when the agent is interrupted. Why now: The published comparison makes these operational dimensions visible across a set of 26 TTS models rather than leaving teams to infer them from vendor claims. The first implication is that Teams should choose test cases around their actual interaction risks—such as interruption handling or reading identifiers—instead of picking a provider from a composite impression.
The evidence boundary is that The benchmark page calls accuracy and naturalness estimates, and says eight voices that cannot take streamed text are excluded from its streaming chart; its figures should not be treated as universal performance guarantees. The page presents comparative results but does not establish that the ranking will hold across languages, regions, voices, or deployment conditions. The first watch condition is whether Whether independent teams reproduce the reported trade-offs on their own scripts, languages, and interruption patterns. A distinct analytical record is warranted because no prior New Runtime record was supplied, and this source adds a specific comparative TTS benchmark rather than a general voice-model announcement.