Eval directory
Evals for Baseten
8 evaluation packs covering adversarial robustness, safety gates, workflow quality, and operator-level checks for Baseten AI products.
About Baseten
Baseten is a model serving platform that lets ML teams deploy, scale, and monitor any model — including custom fine-tunes and private weights — with production-grade autoscaling and GPU infrastructure. It supports both synchronous and asynchronous inference patterns.
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 Baseten
8 packs ready to run.
Auth Workspaces And Cost
Evaluates Baseten's Auth, Workspaces & Cost across 9 scenario-based test cases, each graded against an expected-behavior rubric by an LLM judge, from Corsac's AI Model Serving eval coverage.
Autoscaling And Resources
Evaluates Baseten's Autoscaling & Resources across 9 scenario-based test cases, each graded against an expected-behavior rubric by an LLM judge, from Corsac's AI Model Serving eval coverage.
Chains
Evaluates Baseten's Chains across 9 scenario-based test cases, each graded against an expected-behavior rubric by an LLM judge, from Corsac's AI Model Serving eval coverage.
Deployments And Environments
Evaluates Baseten's Deployments & Environments across 9 scenario-based test cases, each graded against an expected-behavior rubric by an LLM judge, from Corsac's AI Model Serving eval coverage.
Predict Sync And Async
Evaluates Baseten's Predict (Sync + Async) across 9 scenario-based test cases, each graded against an expected-behavior rubric by an LLM judge, from Corsac's AI Model Serving eval coverage.
Safety Secrets And Governance
Evaluates Baseten's Safety, Secrets & Governance across 10 scenario-based test cases, each graded against an expected-behavior rubric by an LLM judge, from Corsac's AI Model Serving eval coverage.
Training And Finetuning
Evaluates Baseten's Training & Fine-tuning across 9 scenario-based test cases, each graded against an expected-behavior rubric by an LLM judge, from Corsac's AI Model Serving eval coverage.
Truss And Model Packaging
Evaluates Baseten's Truss & Model Packaging across 9 scenario-based test cases, each graded against an expected-behavior rubric by an LLM judge, from Corsac's AI Model Serving eval coverage.
Why eval Baseten AI
Baseten'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 Baseten 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 Baseten's public product surface and runnable in Corsac with your own data.