Elise AI
We didn't switch to Sonic 3.5 because it was incrementally better, we switched because nothing else came close… we've seen a 2.9% lift in our conversion and a 12.2% increase in customer engagement.
3 months on us
Introducing Sonic-3.5 and Ink-2.
Build your entire voice stack with one model provider - the only one ranked #1 on both speech and transcription. Don't compromise on quality or speed.
*Terms and conditions here
Ink-2:
Ranked #1 on accuracy, with fast
turn-taking for natural conversations
Sonic-3.5:
Ranked #1 for naturalness, low
latency with support for 40+ languages
Co-designed end to end for voice agents
The only STT and TTS optimized across the full real-time pipeline.
One API, no assembly required
Ship both models in one integration — less vendor stitching, more building.
The tightest loop in voice
Hit sub-90ms TTS and 100ms transcript latency with native turn detection.
Cartesia Sonic-3.5 has become one of the top-performing models for us by combining low latency with natural pacing... helping us deliver strong voice quality across a growing set of languages where other models often fall short.
At Cartesia, we believe the tradeoffs that define today’s voice AI
Speed versus Naturalness,
Accuracy versus Cost,
are largely architectural in origin, not inevitable.
We’ve spent years building and scaling State Space Models because we believe the right primitives eliminate constraints rather than work around them.
And we built Sonic-3.5 and Ink-2 not by optimizing within accepted limits, but by questioning whether those limits need to exist at all.
Our models are designed for live, synchronous interactions, built on State Space Models (SSMs). A new primitive for large-scale foundation models, SSMs deliver ultra-low latency, long-context reasoning, and greater efficiency at scale.
Elise AI
We didn't switch to Sonic 3.5 because it was incrementally better, we switched because nothing else came close… we've seen a 2.9% lift in our conversion and a 12.2% increase in customer engagement.
ServiceNow
Cartesia's state-space models bring enterprise-grade speed and quality to our AI Voice Agents… making it possible for businesses to deploy secure, scalable voice agents that can understand, act, and adapt in real time.
Sierra
Cartesia Sonic 3.5 has become one of the top-performing models for us by combining low latency with natural pacing… helping us deliver strong voice quality across a growing set of languages where other models often fall short.
Callers
Sonic 3.5 has been a meaningful upgrade for Callers… latency and naturalness directly impact conversational flow and user success, and the new model noticeably improves both. We've seen more human interactions — especially in high-volume customer conversations where every millisecond and every turn matters.
Take2 AI
We moved from an incumbent TTS provider to Cartesia because of the support experience. After repeated roadblocks with our previous provider, the difference with Cartesia has been transformative — responsive, technical, and genuinely invested in our success.
Cresta
Sonic 3.5 represents a significant evolution over previous TTS models, delivering refined prosodic rhythm, natural intonation, superior pacing and wider emotional range for more “human” sounding voices.
Bolna
Indian voice agents live or die on whether order IDs, alphanumerics, and multilingual code-switching come out right on a phone line. Sonic 3.5 handles alphanumerics natively… and lands first audio at 100ms p90.
Goodcall
Sonic is the only product in existence with model latency of less than 100 ms, outperforming its next best alternative by a factor of four. This level of performance represents a quantum leap forward.
Quora
Sonic powers audio on Poe across 100+ voices and 14 languages, supporting Quora's millions of users with SOC 2 compliance and unlimited concurrency for enterprise customers.
Fundamento
We run 20M+ outbound calls per month on Cartesia, with peak concurrency of 5,000 calls in a single minute, and 100ms time-to-first-byte — 2x faster than every other voice provider we tested.
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