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Eval Pipeline Cost Landscape: Batching, Caching & Shadow Tests (2D)

2D parameter-space heatmap of an LLM evaluation pipeline: sweep batch size against cache-hit rate to see the full gate-time and cost surface at once, with a live discrete batch-fill gauge and a marker showing your current settings.

AI & Machine Learning2DModerate60 FPS📱 Mobile-adapted⇄ 3D version

Continuous evaluation is what keeps an LLM release pipeline honest, but every test case has to be paid for in both time and money. This 2D companion renders the exact same batching/caching/shadow-routing cost model as an explorable heat field over the (batch size, cache-hit rate) plane, rather than following one settings point through a pipeline scene: every pixel is an independently computed gate-time or cost value, so you can see the whole trade-off surface — including the ridges where a batch just barely fails to fill — at a glance, with a live crosshair for your current sliders and a discrete batch-fill gauge that replays the accumulate-then-fire mechanism in real time.

⚙ Under the hood

llm evaluationbatchingcachingcost optimizationheatmapparameter spacequeueing

2D · HTML5 Canvas 2D · 60 FPS target · runs fully client-side, no install