DeepSeek unveils a V4 model upgrade, accelerating AI responses while reducing serving costs, addressing inference bottlenecks and chip strain in China's competitive AI landscape.

DeepSeek releases DSpark, an open-source speculative decoding framework accelerating DeepSeek-V4 per-user generation 57–85% over MTP-1

DeepSeek's new DSpark framework delivers 60% to 85% faster inference speeds for its V4 models through speculative decoding, with throughput gains up to

Start-up unveils speculative decoding framework that speeds up inference by up to 85 per cent amid China’s push to overcome US AI curbs.

DeepSeek unveils a V4 model upgrade, accelerating AI responses while reducing serving costs, addressing inference bottlenecks and chip strain in China's competitive AI landscape.

DeepSeek DSpark promette un'AI più veloce e meno costosa grazie a una nuova ottimizzazione dell'inferenza, senza creare un nuovo modello.

DSpark can make decoding faster, but acceptance quality still determines how much speed the system actually realizes.

The DeepSeek team announced on Monday that the official release of DeepSeek V4 is scheduled for mid-July. According to the company, the new version builds

Deepseek's new DSpark framework boosts per-user response speed by 60 to 85 percent. A small model proposes token candidates that the larger model checks in batches, squeezing more…