Tencent Open-Sources AngelSpec: A Unified Training Framework for MTP and Block-Parallel Speculative Decoding on Hy3 Models
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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.
1Key Takeaways
- 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.
2AIWedia Score
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3Why it matters
Video AI is reshaping ads, social content, and entertainment with faster generation pipelines. MarkTechPost Video reports that tencent has released AngelSpec, an open-source torch-native framework for training speculative-decoding draft models across six architectures.
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