腾讯刚开源了AngelSpec，一个统一训练推测解码草稿模型的框架。它带的DFly块扩散器能让HY3模型推理快最多2.4倍，还支持六种架构，实用性强。
腾讯开源了AngelSpec，一个基于PyTorch的训练框架，支持6种推测解码架构，包括MTP和块并行方法。该框架引入了DFly块扩散草稿器，采用混合目标条件与隐藏校正自回归头提升生成质量。AngelSpec还集成D-cut机制，实现运行时自适应验证预算分配。在HY3-295B-A21B模型上，TP=8配置下，DFly-8在并发4至64范围内实现1.98至2.40倍的解码速度提升。
Tencent Open-Sources AngelSpec: A Unified Training Framework for MTP and Block-Parallel Speculative Decoding on Hy3 Models
Tencent has released AngelSpec, an open-source torch-native framework for training speculative-decoding draft models across six architectures. It introduces DFly, a block-diffusion drafter with hybrid target conditioning and a hidden-correction autoregressive head, and integrates D-cut for runtime-adaptive verification budgeting. On HY3-295B-A21B with TP=8, DFly-8 delivers a 1.98–2.40× speedup over autoregressive decoding across concurrency 4 to 64. The post Tencent Open-Sources AngelSpec: A Unified Training Framework for MTP and Block-Parallel Speculative Decoding on Hy3 Models appeared first on MarkTechPost .