LLM Model Evaluation
ML/AIRun benchmark suite across multiple models in parallel, compare accuracy/latency/cost, generate data-driven recommendation.
agentclisystem
Why OSOP matters here
Model evaluation is a workflow: prepare test cases, run each model, collect metrics, compare, decide. OSOP records every run so you can track how model performance changes across versions.
Workflow Steps (6)
1
Load Evaluation Dataset
system2
Evaluate Claude
agent3
Evaluate GPT-4
agent4
Evaluate Gemini
agent5
Compare Results
system6
Generate Recommendation
agentConnections (7)
Load Evaluation Dataset→Evaluate Claudeparallel
Load Evaluation Dataset→Evaluate GPT-4parallel
Load Evaluation Dataset→Evaluate Geminiparallel
Evaluate Claude→Compare Resultsparallel
Evaluate GPT-4→Compare Resultsparallel
Evaluate Gemini→Compare Resultsparallel
Compare Results→Generate Recommendationsequential
6
Steps
7
Connections
2
Node Types