4 posts
Small language model or large model? An enterprise decision framework in light of task-based selection, the cost-performance balance, and the hybrid architecture trend.
“Fine-tuning or RAG?” is a false dilemma. The 2026 sequence: Prompt → RAG → Fine-tune → Distill. LoRA/QLoRA, small language models, distillation, and the KVKK-sensitive self-host decision.
Synthetic data solved fine-tuning's data bottleneck. A field guide to generation methods, the practical recipe, model collapse, and Turkish data scarcity.
Fine-tuning shapes behavior; RAG supplies knowledge. The right 2026 order: prompt first, then RAG, then LoRA/QLoRA, distillation last. A field decision guide.