OpenAI Expands GPT-6 Prompt Caching for Cost Reduction

OpenAI has rolled out improved prompt caching capabilities for GPT-6, directly targeting inference cost reduction for developers working with long or repeated context windows. Prompt caching allows repeated portions of prompts to be stored and reused, cutting both latency and token costs in applications that send similar prefixes across many requests. This is particularly impactful for RAG pipelines, multi-turn agents, and applications with large system prompts that remain constant across sessions. Developers should audit their current prompt structures to identify cacheable segments and update their API integration to take advantage of the new behavior. Combined with the Sol and Luna variant releases, OpenAI appears to be systematically lowering the total cost of ownership for GPT-6 production deployments.