The Definitive Guide to Local LLM Inference on Mac: Why Your Machine Is Slow and the Six Fixes That Work
Every Mac owner who has run a local LLM knows the feeling: the model downloads fine, the first answer looks
Tag: GPU
PagedAttention and the KV Cache: How OS Paging Explains Modern LLM Serving
When an LLM serves a 2,000-token response to a prompt of 10,000 tokens, it does something that looks absurd from
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Speculative Decoding: Getting 2-3x More Out of Every GPU Pass
Watch a GPU while a large language model generates text and you’ll see something strange: for most of every forward
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vLLM Prefix Caching: The Prefill Optimization You’re Already Running
Every request that hits an LLM server pays the same tax before the first generated token appears: the prompt must
Continue readingvLLM Prefix Caching: The Prefill Optimization You’re Already Running
Speculative Decoding in vLLM: Draft, Verify, and Cut Latency Without Losing the Distribution
Large language model inference has an awkward performance profile: the GPU does enormous math, then waits. Every token requires a
vLLM v0.23.0: Model Runner V2, Multi-Tier KV Offloading, and the Growing Rust Frontend
The vLLM v0.23.0 release landed last week with 408 commits from 200 contributors, and it packs several changes that directly