Deepseek steigert mit DSpark die Antwortgeschwindigkeit seiner KI-Modelle pro Nutzer um 60 bis 85 Prozent. Das Verfahren nutzt Speculative Decoding: Ein kleines Modell schlägt Token-Kandidaten vor, die das große Modell gebündelt prüft. Die Effizienzgewinne könnten Chinas Abhängigkeit von US-Hochleistungschips weiter verringern.

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.

Deepseek steigert mit DSpark die Antwortgeschwindigkeit seiner KI-Modelle pro Nutzer um 60 bis 85 Prozent. Das Verfahren nutzt Speculative Decoding: Ein kleines Modell schlägt…

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…

Non è l’unico, ma la lentezza nelle risposte resta uno dei limiti più sentiti dei modelli linguistici, specie a livello di data center. DSpark la riduce su DeepSeek-V4, e DeepSpec…

DeepSeek's new DSpark framework delivers up to 400% inference speed gains via software alone, potentially undermining demand for Nvidia's premium GPU