1. Leverage Prompt Caching
Modern AI models like DeepSeek, Gemini, and Anthropic support prompt caching. By caching large contexts (docs, system instructions), you can reduce input costs by up to 90% for subsequent calls.
2. Implement Smart Model Routing
Not every task requires GPT-4o. Route simpler tasks like summarization or basic extraction to lower-cost models like DeepSeek-V3 or Gemini 1.5 Flash. According to LegoStack simulations, this can save 40-60% of infrastructure costs.
3. Token-Efficient Architecture
Enforcing strict JSON output and trimming system prompts can reduce token usage by over 20%. Regular monitoring of token consumption is key to sustainable AI scaling.