KV caching, clearly explained:
You're in an ML Engineer interview at OpenAI. The interviewer asks: "Our GPT model generates 100 tokens in 42 seconds. How do you make it 5x faster?" You: "I'll optimize the model architecture and use a better GPU." Interview over. Here's what you missed:

Oct 22, 2025 路 9:18 AM UTC

Replying to @akshay_pachaar
KV caching is just save the preprocessed prompt. Nothing to explain :)
1
Replying to @akshay_pachaar
Bookmarked!
Replying to @akshay_pachaar
KV caching is a game changer for LLMs. I wrote a case study on how it helps with enterprise AI adoption. 馃悽馃挧