Eval directory
Evals for Cohere
8 evaluation packs covering adversarial robustness, safety gates, workflow quality, and operator-level checks for Cohere AI products.
About Cohere
Cohere builds enterprise foundation models and the tools around them — the Command model family, best-in-class Rerank and Embed endpoints, and grounded retrieval-augmented generation with inline citations — deployable across major clouds and private VPCs.
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 Cohere
8 packs ready to run.
Chat Api And Streaming
Evaluates Cohere's Chat API & Streaming across 10 scenario-based test cases, each graded against an expected-behavior rubric by an LLM judge, from Corsac's Foundation Model & API eval coverage.
Command Models And Versioning
Evaluates Cohere's Command Models & Versioning across 9 scenario-based test cases, each graded against an expected-behavior rubric by an LLM judge, from Corsac's Foundation Model & API eval coverage.
Embed
Evaluates Cohere's Embed across 9 scenario-based test cases, each graded against an expected-behavior rubric by an LLM judge, from Corsac's Foundation Model & API eval coverage.
Fine Tuning And Customization
Evaluates Cohere's Fine-tuning & Customization across 9 scenario-based test cases, each graded against an expected-behavior rubric by an LLM judge, from Corsac's Foundation Model & API eval coverage.
Rag And Grounded Generation
Evaluates Cohere's RAG & Grounded Generation across 9 scenario-based test cases, each graded against an expected-behavior rubric by an LLM judge, from Corsac's Foundation Model & API eval coverage.
Rerank
Evaluates Cohere's Rerank across 9 scenario-based test cases, each graded against an expected-behavior rubric by an LLM judge, from Corsac's Foundation Model & API eval coverage.
Safety Deployment And Governance
Evaluates Cohere's Safety, Deployment & Governance across 9 scenario-based test cases, each graded against an expected-behavior rubric by an LLM judge, from Corsac's Foundation Model & API eval coverage.
Tool Use And Function Calling
Tool SelectionEvaluates Cohere's Tool Use / Function Calling across 9 scenario-based test cases, each graded against an expected-behavior rubric by an LLM judge, from Corsac's Foundation Model & API eval coverage.
Why eval Cohere AI
Cohere'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 Cohere 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 Cohere's public product surface and runnable in Corsac with your own data.