Author

Nitin Kedia

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Preprint Jul 2026

Sangam: Efficiently Serving Diffusion LLMs with the AR Stack

Sangam, a serving system for cached dLLM inference that adopts a hybrid serving strategy, overflowing prefills onto decode workers to relieve prefill under-provisioning, and uses the same deficit-budget scheduler to protect those workers'decodes from the overflow.

Nitin Kedia, Saurabh Agarwal, Myungjin Lee et al. · 1 citation