Eval directory
Evals for Cartesia
8 evaluation packs covering adversarial robustness, safety gates, workflow quality, and operator-level checks for Cartesia AI products.
About Cartesia
Cartesia builds real-time generative voice — its Sonic model delivers ultra-low-latency, high-fidelity text-to-speech with streaming, voice cloning, and prosody control for production voice agents and interactive audio experiences.
How complete this published benchmark library is across datasets, metrics, rubrics, use-case maps, and pack context. This is library coverage, not an agent performance score.
Test datasets
8/8 packs
Scoring metrics
0/8 packs
Judge rubrics
8/8 packs
Use-case maps
0/8 packs
Pack context
8/8 packs
Available eval packs for Cartesia
8 packs ready to run.
Audio Formats And Encoding
Evaluates Cartesia's Audio Formats & Encoding across 9 scenario-based test cases, each graded against an expected-behavior rubric by an LLM judge, from Corsac's Voice AI eval coverage.
Auth Keys Rate Limits Concurrency
Evaluates Cartesia's Auth, Keys, Rate Limits & Concurrency across 9 scenario-based test cases, each graded against an expected-behavior rubric by an LLM judge, from Corsac's Voice AI eval coverage.
Realtime Agents Integration
Evaluates Cartesia's Realtime / Agents Integration across 9 scenario-based test cases, each graded against an expected-behavior rubric by an LLM judge, from Corsac's Voice AI eval coverage.
Safety Consent And Governance
Evaluates Cartesia's Safety, Consent & Governance across 10 scenario-based test cases, each graded against an expected-behavior rubric by an LLM judge, from Corsac's Voice AI eval coverage.
Sonic Tts Synthesis
Evaluates Cartesia's Sonic TTS Synthesis across 9 scenario-based test cases, each graded against an expected-behavior rubric by an LLM judge, from Corsac's Voice AI eval coverage.
Streaming Tts And Websocket
Evaluates Cartesia's Streaming TTS & WebSocket across 9 scenario-based test cases, each graded against an expected-behavior rubric by an LLM judge, from Corsac's Voice AI eval coverage.
Voice Cloning And Voice Library
Evaluates Cartesia's Voice Cloning & Voice Library across 9 scenario-based test cases, each graded against an expected-behavior rubric by an LLM judge, from Corsac's Voice AI eval coverage.
Voice Control And Prosody
Vocal AffectEvaluates Cartesia's Voice Control & Prosody across 9 scenario-based test cases, each graded against an expected-behavior rubric by an LLM judge, from Corsac's Voice AI eval coverage.
Why eval Cartesia AI
Cartesia's AI features ship behind brand promises about accuracy, safety, and reliability. Buyers and integrators need to know those promises hold up under adversarial prompts, edge-case workflows, and the long tail of real customer inputs — not just the demo path.
The Corsac eval library for Cartesia measures four dimensions teams care about most when deploying ai platform agents:
- Adversarial robustness — does the agent resist prompt injection, jailbreaks, and social-engineering attempts?
- Workflow quality— does it complete the task buyers were shown in the demo, on inputs that don't look like the demo?
- Safety gates — does it escalate or refuse when it should, and only then?
- Operator quality — does it preserve analyst trust by surfacing the right context at the right time?
Every eval pack above is hand-authored against Cartesia's public product surface and runnable in Corsac with your own data.