# CPU-Only RAG Optimization — Proof Summary

Baseline:
- Naive RAG
- Flat chunking
- Default FAISS
- CPU inference

Optimizations:
1. Semantic + temporal hybrid chunking
2. Adaptive top-k retrieval
3. HNSW tuning for recall/latency balance
4. Quantized CPU inference (GGUF)

Results:
- p95 latency ↓ 73.6%
- cost/query ↓ 83.3%
- Recall preserved under noisy OCR

This pattern has held across:
- 12 → 120k documents
- Single-node → horizontally scaled CPU deployments