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Taking vLLM Apart: A Practical Guide to Disaggregated Serving

vLLM Blog · published 29 September 2026

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Links from this post

Link
Host
https://github.com/llm-d/llm-d/tree/main/guides/pd-disaggregation
github.com
https://github.com/vllm-project/vllm/issues/43094
github.com
https://llm-d.ai/?ref=danmackinlay.name
llm-d.ai
https://github.com/ai-dynamo/dynamo
github.com
https://kserve.github.io/website/
kserve.github.io
https://github.com/vllm-project/production-stack
github.com
https://github.com/vllm-project/aibrix
github.com
https://github.com/vllm-project/vllm/issues/57571
github.com
https://github.com/vllm-project/vllm/pull/47931
github.com
https://github.com/vllm-project/vllm/issues/57574
github.com
https://github.com/vllm-project/vllm/issues/56851
github.com
https://github.com/vllm-project/vllm/issues/42729
github.com
https://github.com/vllm-project/vllm/issues/47161
github.com
https://github.com/vllm-project/vllm/issues/22817
github.com
https://github.com/vllm-project/vllm/issues/34407
github.com
Elsewhere on vllm.ai (13)
https://vllm.ai/blog/2025-09-05-anatomy-of-vllm
vllm.ai
https://docs.vllm.ai/en/latest/features/disagg_prefill/
docs.vllm.ai
https://vllm.ai/blog/2025-12-15-vllm-epd
vllm.ai
Announcing vLLM AFD Plugin: Disaggregating Attention and FFN for Flexible MoE Serving Read at the source (opens in a new tab)
vllm.ai
https://vllm.ai/blog/2026-04-21-hybrid-ssm-disagg
vllm.ai
https://vllm.ai/blog/2026-04-07-moriio-kv-connector
vllm.ai
PD Serving of Qwen3.8-2.4T Read at the source (opens in a new tab)
vllm.ai
https://vllm.ai/blog/2026-09-30-bidirectional-kvxfer-multiturn-agentic-workload
vllm.ai
Serving Agentic Workloads at Scale with vLLM x Mooncake Read at the source (opens in a new tab)
vllm.ai
vLLM x TileRT: Specialized Decode for Latency-Critical Serving Read at the source (opens in a new tab)
vllm.ai
https://docs.vllm.ai/en/latest/features/nixl_connector_usage/
docs.vllm.ai
https://docs.vllm.ai/en/latest/serving/online_serving/renderer/
docs.vllm.ai
https://docs.vllm.ai/en/latest/serving/online_serving/derenderer/
docs.vllm.ai