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AngelSpec introduces a unified training and inference framework for speculative decoding that jointly optimizes autoregressive multi-token prediction and block-parallel diffusion drafters to handle heterogeneous real-world workloads. Experiments on the Hy3 model series show up to 2.4x speedup over autoregressive decoding and 11.8% higher throughput than DFlash.