Sovereign SLM vs Frontier LLM TCO: An Illustrative 74% Cost-Reduction Model

import time
from typing import Dict, Any

class SemanticCostOptimizer:
    def __init__(self, local_slm_client, cloud_frontier_client, complexity_classifier):
        self.slm = local_slm_client
        self.frontier = cloud_frontier_client
        self.classifier = complexity_classifier

    async def execute_query(self, prompt: str, system_prompt: str) -> Dict[str, Any]:
        # Step 1: Sub-millisecond complexity analysis
        complexity_score = self.classifier.score(prompt)
        
        # 90%+ queries (extraction, classification, summarization) handled by local SLM
        if complexity_score < 0.75:
            start_time = time.time()
            response = await self.slm.generate(prompt=prompt, system_prompt=system_prompt)
            duration = time.time() - start_time
            
            return {
                "response": response,
                "tier": "SOVEREIGN_SLM",
                "cost_usd": 0.00018, # Compute amortization only
                "latency_ms": round(duration * 1000, 2),
                "data_egress": False
            }
        else:
            # Complex ambiguous reasoning routed to frontier model
            response = await self.frontier.generate(prompt=prompt)
            return {
                "response": response,
                "tier": "FRONTIER_API",
                "cost_usd": 0.0125,
                "latency_ms": 780.0,
                "data_egress": True
            }