Fine-Tuned 0.6B Router Beats Its 27B Sibling: Small Specialized Models Win
mshubham · reddit · 2026-10-16
A developer fine-tuned vLLM-SR's d3-edge (0.6B) with simple SFT + LoRA on just a few thousand examples, and it outperformed the 45x larger d3 (27B) on routing decisions.
- Typed Decisions (structured decision-making): 42.2% → 79.2% after fine-tuning, beating 27B's 74.4%
- Banking77 (77-class intent classification): 89.5% → 91.7%, nearly matching 27B's 92.2%
The takeaway: fine-tune small specialized decision models instead of using large general-purpose models for every task. A reproducible Colab is included.
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