Feeding Massive Structured Context to LLMs: Caching vs RAG
Firm-Track3617 · reddit · 2026-07-07
A developer building a platform requiring LLMs to reference numerous existing nodes (such as correctly citing many previously defined nodes when generating a DAG) sought advice on balancing latency, cost, and inference quality.
The author considered using context caching when most context remains unchanged across requests, but also explored using a vector database for RAG, expressing concerns over the model needing to reference a massive number of nodes rather than just retrieving a few semantically similar items.
They are looking for industry experiences and recommendations on enabling LLMs to access massive amounts of structured context.
Related event: Developers Debate: Context Caching vs. RAG for Massive LLM Contexts(3 posts)→
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