Token Blaster
Cost-aware AI orchestration.
A model-routing concept that evaluates task complexity, model cost, estimated output quality and validation needs before generation. It explores compression, reuse, reasoning depth and quality constraints to select an appropriate execution route.
Cost-first model selection
A defined component within the proposed architecture, intended to support more reliable decisions and clearer system behaviour.
Quality and rework thresholds
Structured processing and explicit criteria guide selection, interpretation or optimisation.
Compression and reuse strategies
An area for progressive engineering, evaluation and refinement as the technology is developed.
The challenge.
Using the same model and compute budget for every request can waste resources or reduce output quality.
How it works.
A cost-first routing prototype searches combinations of model choice, compression, reuse, reasoning depth and validation under estimated quality constraints.
Conceptual workflow, not a production system diagram.
Development position.
Code prototype for route scoring and selection; model quality and cost assumptions are illustrative, not live measured results.
Where it may apply.
Content pipelines, AI service orchestration, production workflow design and cost governance.
Questions still open.
Quality estimates must be calibrated on real evaluations; compression and reuse must preserve task meaning and safety.