Strengths
- Improves benchmark performance when added to models like DeepSeek-V3.
- Achieves higher code accuracy (95% at n=4 vs. 80% at n=1).
- Enhances data efficiency via denser training signals.
- Enables speculative decoding for faster inference in GLM-4.5.
- Compatible with efficient mixture-of-experts architectures.
Limitations
- No centralized official website or single repository for Multi-Token Prediction as it is a research technique.
- Limited open-source implementations; main research code (MuToR) is pending full upload.