DeepSeek releases DSpark paper describing speculative decoding techniques to speed up large language model inference

DeepSeek has published a DSpark paper on GitHub focused on using speculative decoding to accelerate LLM inference. The available article content provides little detail beyond the paper listing, repository metadata, and download link.

The work points to continued industry focus on reducing inference latency and cost as LLM usage scales. If DSpark improves throughput without degrading output quality, it could make real-time AI applications more practical and economical.