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long-context

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REQUEST TO TOKENS · 041 LAYER IN 4 KEEPS EVERY TOKEN
request-to-tokenskv-cacheattention

When Most Layers Stop Caching: Hybrid, Sliding, and Sparse Attention, Sized

Why a 27B model holds 262k tokens of context on a 24 GB GPU: what hybrid, sliding-window, and sparse attention store and read per token, on real models.

by The Serving Stack
QUANTIZATION · 10BF16 · 498K TOKENSFP8 · 975K4-BIT · 1.84MSAME TOKENS, FEWER BYTES
quantizationkv-cachevllm

Quantizing the KV Cache: FP8 and Below

Seven KV cache formats in vLLM, from FP8 to 3-bit, on one model: how many more tokens fit, what long-context recall loses, and why speed follows the kernel.

by The Serving Stack

Inference Notes

Once a week: what changed in serving AI models, and what it means if you build, run or pay for them, in about five minutes.

The Serving Stack

Inference Engineering, In Depth

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