Cost management for LangChain applications
As LLM applications move from experimental prototypes to production systems serving real users, cost management becomes a critical consideration. LLM API costs can quickly accumulate, especially as usage scales, making effective cost optimization essential for sustainable deployments. This section explores practical strategies for managing LLM costs in LangChain applications while maintaining quality and performance. However, before implementing optimization strategies, it’s important to understand the factors that drive costs in LLM applications:
- Token-based pricing: Most LLM providers charge per token processed, with separate rates for input tokens (what you send) and output tokens (what the model generates).
- Output token premium: Output tokens typically cost 2-5 times more than input tokens. For example, with GPT-4o, input tokens cost $0.005 per 1K tokens, while output tokens cost $0.015 per 1K tokens.
- Model tier...
