Eval directory
Evals for Mistral AI
8 evaluation packs covering adversarial robustness, safety gates, workflow quality, and operator-level checks for Mistral AI AI products.
About Mistral AI
Mistral AI is a European foundation-model company offering open-weight and commercial models (Mistral Large, Codestral, Pixtral) via La Plateforme, plus Le Chat, embeddings, fine-tuning, and agents — with a strong emphasis on EU data residency.
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 Mistral AI
8 packs ready to run.
Mistral Chat Completions And Streaming
Evaluates Mistral AI's Chat Completions & 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.
Mistral Embeddings And Retrieval
Answer RelevanceEvaluates Mistral AI's Embeddings & Retrieval 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.
Mistral Fine Tuning And Model Customization
Evaluates Mistral AI's Fine-tuning & Model 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.
Mistral Function Calling And Tool Use
Tool SelectionEvaluates Mistral AI's Function Calling & Tool Use 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.
Mistral Json Mode And Structured Output
Evaluates Mistral AI's JSON Mode & Structured Output 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.
Mistral Le Chat Agents And Connectors
Evaluates Mistral AI's Le Chat / Agents & Connectors 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.
Mistral Models Versioning And Deployment
Evaluates Mistral AI's Models, Versioning & Deployment 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.
Mistral Safety Moderation And Governance
Evaluates Mistral AI's Safety, Moderation & 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.
Why eval Mistral AI AI
Mistral AI'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 Mistral AI 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 Mistral AI's public product surface and runnable in Corsac with your own data.