vLLM adds an experimental plugin to split attention and FFN serving
vllm_project · x · 2026-07-24
vLLM introduced an experimental AFD Plugin that implements Attention-FFN disaggregation for MoE serving.
- Attention and expert/FFN workloads have different scaling needs, so the plugin splits them into separate services instead of forcing one shared topology.
- The design keeps the same vLLM serving surface and avoids a fork.
- It targets both NVIDIA GPUs and Ascend NPUs.
The attached architecture diagram shows entry points for OpenAI-compatible APIs and vLLM serve, plus separate attention, AFD connector, and FFN roles.
Related event: vLLM Releases Experimental AFD Plugin to Boost MoE Inference(3 posts)→
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