Tencent Open-Sources AngelSpec: Unified Training Framework for Speculative Decoding on MoE Models

Tencent has released AngelSpec as an open-source framework that unifies Multi-Token Prediction (MTP) training and block-parallel speculative decoding, specifically targeting their Hy3 Mixture-of-Experts model architecture. Speculative decoding is a key inference acceleration technique, and AngelSpec's block-parallel approach allows multiple speculative tokens to be verified simultaneously, improving throughput compared to sequential verification methods. By open-sourcing the framework, Tencent is making these efficiency gains accessible to teams training or fine-tuning large MoE models outside of proprietary infrastructure. For ML engineers working on inference optimization or MoE training pipelines, AngelSpec is worth evaluating as a drop-in or reference implementation for accelerating both training and serving. The release positions Tencent as a meaningful contributor to open-source efficiency tooling for frontier-scale models.