Token-Budget-Aware LLM Reasoning: Cut Costs in 2026

Introduces token-budget-aware LLM reasoning (TALE) as a cost-saving mechanism. Details prompt-level techniques like Chain-of-Thought (CoT), Chain of Draft, and TALE Estimation + Prompting, including their effectiveness and limitations. Discusses API-level budget controls in Gemini and Claude. Proposes architectural solutions: semantic caching (with Redis Iris/LangCache) for repeated queries and complexity-based routing for model selection. Highlights Redis Iris/LangCache for semantic caching and RedisVL SemanticRouter for routing.