Ludion
liveOptimize LLM inference costs by routing browser-sized tasks on-device
Details
Routes low-risk LLM inference tasks to WebLLM in user browsers while retaining server fallback for complex workflows. Measures real device capabilities rather than relying on WebGPU flags to avoid sending small/cheap tasks to cloud. Integrates with existing server architecture for hybrid on-device/cloud execution
Best fit users
- •AI application developers
- •WebGPU-capable device operators
- •Cloud cost optimization teams
Why this one made the cut
Modern AI apps waste cloud resources processing tasks that could run locally. WebGPU support detection is unreliable across devices/browsers. Ludion's measurement-based routing prevents payment of cloud prices for work that could execute efficiently in the browser
What makes it different
Uniquely measures actual model execution rather than trusting capability flags. Implements intelligent policy-based routing decisions between browser and server rather than assuming all browser claims are valid for inference workloads