KV Cache
7 articles tagged with this topic
How LRU Cache Became LLM Infrastructure's Secret Backbone
LeetCode #146 solution went viral this week. That hashmap+linked-list algorithm underpins LLM KV Cache, vector DBs, and Agent memory—AI's speed/cost b
Qwen Users Roast Reasoning Models: 50% of 'Thinking' Is Just 'Wait' Tokens
Reddit joke exposes a real problem: reasoning models' thinking chains are filled with filler like 'wait', bloating KV cache and exploding deployment c
Token Prices Dropped 90% in 2 Years — Here's Why LLM Inference Is Now Cheap
Why are some AI assistants free and others costly? We unpack Token, Transformer, and KV Cache—the hidden cost drivers behind every query.
16GB GPU Hits 'Performance Cliff' Running Qwen — Local LLM Bar Is Higher Than You Think
A Reddit user found Qwen3-27B's KV cache precision tweak on a 16GB GPU cratered speed from 9 to 1.5 tokens/sec. Local LLM deployment is far harder tha
Independent KV Cache Evaluation SDK Signals Shift to Inference Infrastructure
KV cache dominates VRAM in long-context inference. An independent evaluation SDK for TurboQuant signals the shift from "can it run?" to "how to run st
Microsoft 4x LLM Inference: AI's Second Half Is Cutting Infra Costs
At NSDI 2026, Microsoft unveils AI infra breakthroughs like 4x LLM inference via cache sharing. AI competition shifts from scaling parameters to infra
80M Tokens for 4 RMB: DeepSeek Disk Cache Rewrites LLM Inference Costs
DeepSeek's novel architecture enables disk-level caching, slashing API costs 10x. This signals LLM inference shifting from raw compute to engineering