The use case: how Cartesia deploys Together AI
Cartesia runs production real-time voice serving and model training on Together AI's GPU clusters. It operates a custom inference engine for its State Space Model architecture with cluster-level access, and uses PCI-compliant environments for regulated enterprise customers.
In the customer’s words
Because our voice models use state space architectures, we need to run a purpose-built inference engine. Together AI gives us the compute and cluster-level access we need—down to the filesystem and SSH permissions—so we can optimize our serving stack exactly how we want. They manage the heavy lifting of the hardware orchestration and ingress, and we get the low-level control required to hit our streaming latency targets.Other AI tools used by Cartesia
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Together AI users in Artificial Intelligence
Companies in the same sector, with public evidence.
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LegionEdgeConfirmedGo straight to the source
Based on Together AI’s published case study. We check the public evidence; the results are reported by the vendor.
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- Oct 3, 2026
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Cartesia reports 90ms model latency for voice generation across the Sonic model family, achieving the fast, consistent response times required for streaming conversational AI.