Logic42 Lab
A research laboratory focused on optimizing edge AI inference. It studies the combination of decision models with RAG architectures to improve the performance of small edge models.
Timeline (last 90 days)
Logic42 Lab conducted a 324-run full-factorial experiment showing that introducing a decision model for intent routing before generation can make edge small models under 7B reach production-grade usability while cutting enterprise cloud spending by 79.1%.
The 80/20 hybrid routing strategy routes 80% of routine queries to edge SLMs and reserves frontier cloud models for 20% of ambiguous cases, which according to Logic42 Lab's FinOps scale model can achieve a 79.1% net cost reduction.
Logic42 Lab founder Asif Muhammad Iqbal said that reducing the number of output tokens is the only physical mechanism for accelerating generation on local edge hardware, and you cannot cheat GPU memory bandwidth.
All Facts (3)
Logic42 Lab conducted a 324-run full-factorial experiment showing that introducing a decision model for intent routing before generation can make edge small models under 7B reach production-grade usability while cutting enterprise cloud spending by 79.1%.
50%UnverifiedThe 80/20 hybrid routing strategy routes 80% of routine queries to edge SLMs and reserves frontier cloud models for 20% of ambiguous cases, which according to Logic42 Lab's FinOps scale model can achieve a 79.1% net cost reduction.
50%UnverifiedLogic42 Lab founder Asif Muhammad Iqbal said that reducing the number of output tokens is the only physical mechanism for accelerating generation on local edge hardware, and you cannot cheat GPU memory bandwidth.
50%