The Hidden Behavior of LLMs – Prompt Caching and Determinism

Go beyond the “stateless” myth. This deep dive into Prompt Caching (OpenAI, Gemini, Anthropic) explains the essential difference between caching the input and generating a fresh output, revealing why LLM responses vary even at a strict Temperature=0. We analyze the technical physics behind this non-determinism (MoE architecture, GPU math) and share a crucial developer insight: why adding a single word to your prompt can suddenly fix a sequence of consistently flawed code generations, ensuring you optimize your agentic workflows for maximum speed and quality.

 

​ Go beyond the “stateless” myth. This deep dive into Prompt Caching (OpenAI, Gemini, Anthropic) explains the essential difference between caching the input and generating a fresh output, revealing why LLM responses vary even at a strict Temperature=0. We analyze the technical physics behind this non-determinism (MoE architecture, GPU math) and share a crucial developer insight: why adding a single word to your prompt can suddenly fix a sequence of consistently flawed code generations, ensuring you optimize your agentic workflows for maximum speed and quality.   Read More Technology Blog Posts by SAP articles 

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