1️⃣ Generates multiple draft tokens in parallel with a single forward pass. 2️⃣ A lightw…

1️⃣ Generates multiple draft tokens in parallel with a single forward pass. 2️⃣ A lightweight sequential module quickly refines those drafts by injecting token dependencies. 3️⃣ Each token receives a confidence score, estimating how likely it is to survive verification. 4️⃣ A hardware-aware scheduler decides how many tokens are actually worth verifying, based on confidence and current GPU load. 5️⃣ The target model verifies only the most promising candidates, while GPU resources are immediately reallocated to other requests. 👉 Less wasted verification. Higher GPU utilization. Same output quality. However, DeepSeek continues to show that some of the biggest gains in LLM serving don't come from larger models—but from smarter systems. 🔗 Full analysis: #DeepSeek #DSpark #LLM #AIInfra #Inference #AI #Tech