The KV Cache: Why LLM Serving Is a Memory Problem
Every LLM serving stack lives or dies by one data structure most developers never see: the KV cache. It is
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Tag: Attention
MHA, MQA, GQA, MLA: The KV-Cache Trade-offs Behind Every Modern Transformer
Ask someone to sketch a transformer on a whiteboard and they’ll draw the 2017 version: softmax attention over every pair
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DeepSeek V4.1-Flash, Explained Like You’re New: KV Caches, MoE, and the 890-Byte Trick
DeepSeeded? No — DeepSeek. In September 2026 the Chinese AI lab released a paper titled “DeepSeek-V4.1-Flash: Pushing the Limits of
DeepSeek-V4.1-Flash: Why the Most Interesting AI Paper This Month Is About Storage
Serving a large language model to thousands of concurrent users is, underneath all the marketing, a memory management problem. Every
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Metis: The First Memory Foundation Model That Learns to Remember
AI agents have gotten remarkably good at reasoning, perceiving, and acting. But ask one to remember what you told it
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How MiniMax Sparse Attention Achieves 28x Compute Reduction at 1M Context Length
The attention mechanism is the backbone of every transformer model, but it carries a brutal cost: quadratic complexity with respect
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