Eval directory
Evals for Groq
8 evaluation packs covering adversarial robustness, safety gates, workflow quality, and operator-level checks for Groq AI products.
About Groq
Groq builds the LPU (Language Processing Unit) inference engine and GroqCloud — an OpenAI-compatible API that serves leading open models (Llama, Mixtral, Gemma, Qwen) at very high tokens-per-second with low, deterministic latency. Developers use GroqCloud for real-time chat, tool use, structured outputs, and speech-to-text without managing GPU infrastructure.
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 Groq
8 packs ready to run.
Auth Rate Limits And Tiers
Evaluates Groq's Auth, Rate Limits & Tiers across 9 scenario-based test cases, each graded against an expected-behavior rubric by an LLM judge, from Corsac's Fast Inference eval coverage.
Batch Api
Evaluates Groq's Batch API across 9 scenario-based test cases, each graded against an expected-behavior rubric by an LLM judge, from Corsac's Fast Inference eval coverage.
Chat Completions Openai Compatible
Evaluates Groq's Chat Completions (OpenAI-compatible) across 9 scenario-based test cases, each graded against an expected-behavior rubric by an LLM judge, from Corsac's Fast Inference eval coverage.
Function Calling And Tool Use
Tool SelectionEvaluates Groq'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 Fast Inference eval coverage.
Safety Models And Governance
Evaluates Groq's Safety, Models & Governance across 10 scenario-based test cases, each graded against an expected-behavior rubric by an LLM judge, from Corsac's Fast Inference eval coverage.
Speech Whisper Stt
Transcription AccuracyEvaluates Groq's Speech (Whisper STT) across 9 scenario-based test cases, each graded against an expected-behavior rubric by an LLM judge, from Corsac's Fast Inference eval coverage.
Speed Streaming And Latency
Evaluates Groq's Speed, Streaming & Latency across 9 scenario-based test cases, each graded against an expected-behavior rubric by an LLM judge, from Corsac's Fast Inference eval coverage.
Structured Outputs And Json Mode
Evaluates Groq's Structured Outputs & JSON Mode across 9 scenario-based test cases, each graded against an expected-behavior rubric by an LLM judge, from Corsac's Fast Inference eval coverage.
Why eval Groq AI
Groq'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 Groq 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 Groq's public product surface and runnable in Corsac with your own data.