LLM Orchestrator
A working replication of NVIDIA's “Small Language Models are the Future of Agentic AI” — their six-step LLM→SLM conversion pipeline, run twice on my own agent telemetry. A converted 3.2 GB model beats a purpose-built 9.5 GB one 0.82 to 0.62 on a 61-task held-out set, and two different model families land on the same score — so the result belongs to the pipeline, not one lucky checkpoint. Every verdict came from a gate fixed before the run.
- Python
- SLM research replication
- llama.cpp · 35B local
- Claude API
- evals + telemetry