32 minutesFast LLM Serving with vLLM and PagedAttention
Understand why serving engines, batching and KV-cache memory dominate self-hosted inference economics.
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Is This the End of RAG? Anthropic's NEW Prompt Caching
Prompt Engineering. Walks through Anthropic's prompt caching against Gemini's context caching with concrete latency-and-cost reductions per use case (long-document chat, few-shot, multi-turn). The breakdown of cache-write surcharge vs. cache-read discount is exactly what the article assumes when it talks about when caching pays off.
AI Expert note
Recorded in August 2024, so the model names and per-token prices are dated. The cache-write-surcharge vs. cache-read-discount mechanic still holds; check current provider pricing pages before running the numbers for your workload.
What you should get from this
You can estimate when prompt caching pays off by weighing cache-write surcharges against read savings for your real workloads.
Watch or know first
Working knowledge of LLM API pricing and long-prompt workloads.
Last reviewed: May 18, 2026
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