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A cascaded voice agent just won a blind human-preference ranking against native speech-to-speech models.
Today, Cartesia launched Managed Agents, ranked #1 on Artificial Analysis’ Speech Agent Arena.
Most LLMs learn from chunks of text picked by a tokenizer. But here, H-Nets learn directly from raw bytes and figure out those boundaries themselves.
This leads to 3–5x better efficiency in controlled scaling experiments. At larger scale, matching an open-source model trained on 11 trillion tokens with roughly 10x less training data and compute.
> #1 in blind human preference and #1 in enterprise accuracy > Cascaded stack that sounds as natural as speech-to-speech > Own speech models and agent harness tuned as one system
Introducing Cartesia Managed Agents: our end-to-end voice agent platform for enterprise.
#1 on @ArtificialAnlys Speech Agent Arena and @ServiceNow EVA-Bench, built by co-designing our voice models and harness as one system.
Check it out → https://t.co/7kJhCYqjQo https://t.co/NVOAds9czf
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