Accelerating OpenClaw Agents with CacheBlend

The standard approach to reducing LLM inference costs is prefix caching, which reuses previously computed token states to avoid redundant computation. In practice, however, this approach misses significant caching opportunities in real-world agentic workloads! Caching in Agentic Workflows In agentic workloads, shared content (e.g., retrieved contexts and documents) frequently appears across requests at varied positions,…

https://blog.lmcache.ai/en/2026/04/01/accelerating-openclaw-agents-with-cacheblend/