How DeepSeek’s DSpark Makes LLMs 85% Faster Without Retraining

DeepSeek’s latest development, DeepSpark, introduces a speculative decoding method that significantly enhances the speed of large language models (LLMs) without compromising their accuracy. As explained by Prompt Engineering, this technique uses a dual-model system: a smaller, faster draft model generates token blocks in parallel, while a larger target model verifies these blocks in a single […]
The post How DeepSeek’s DSpark Makes LLMs 85% Faster Without Retraining appeared f