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Smart Task Routing & Execution Tiers

Not every turn needs the same amount of model. Wizard classifies each one and dispatches it to a model sized for that specific task, rather than routing everything through the same heavyweight pair — see Architecture for what the manager, worker, and optional vision roles (MODEL_NAME, WORKER_MODEL_NAME, VISION_MODEL_NAME) each do.


Task Complexity Classifier

Rather than routing every single turn through heavy reasoning models, the Task Router inspects the user query and dataset context to classify the task into three complexity tiers:

TierCharacteristicsExample OperationsTarget Model
LIGHTWEIGHTDirect schema queries, metadata extraction, column definitions, simple formatting."What columns are in this table?", "Show table summary"Small fast model (1.5B3B) or fast local model.
STANDARDSingle-pass transformations, basic statistics, standard filtering and aggregations."What is the average tip by day?", "Filter orders where status = shipped"Balanced instruct model (7B8B).
REASONING_HEAVYMulti-table joins, hypothesis validation, anomaly investigation, complex ML modeling."Which user cohorts drive churn and why?", "Train a forecast model on sales"Frontier / Deep Reasoning model (7B+ coder + reasoning manager).

Dynamic Turn Downscaling

When a user has multiple local models installed (e.g., both qwen2.5:3b and a larger qwen2.5:14b), Wizard automatically routes LIGHTWEIGHT sub-tasks to the faster model while preserving the primary model for REASONING_HEAVY investigation.

This produces:

  • Instant Response Times: Simple questions answer in under 2 seconds.
  • Lower Resource Consumption: Minimizes token burn and CPU/GPU memory swapping.
  • Uncompromised Quality: Complex analytical depth remains available whenever required.
Reviewed for Wizard v1.0.2Edit this page on GitHub