Track 16 — Executive Playbooks & Guides
16-1: How to Deploy Small Language Models (SLMs)
The complete playbook for running local, quantized inference to bypass API monopolization.
3 Lessons~45 min
🎯 What You'll Learn
- ✓ Mastering 4-bit and 8-bit QLoRA strategies
- ✓ Deploying Llama.cpp and Ollama inside enterprise perimeters
- ✓ Cost reduction mapping from GPT-4o to Llama 3 8B
Free Preview — Lesson 1
1
Introduction: The API Margin Tax
Relying exclusively on hyperscalers for LLM inference introduces a permanent Margin Tax on your product. Every request costs compute. By deploying Small Language Models (SLMs) locally, you sever the transaction cost.
Inference Margin
The compounding cost of per-token API billing over a 36-month horizon.
Zero-Cost Edge
📝 Exercise
Identify your three highest-volume AI primitives. Could they be resolved by an 8B perimeter model?
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