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SenseTime details SenseCore architecture for agentic inference

By PulseAugur Editorial · [1 sources] ·

SenseTime has detailed its SenseCore architecture, which separates prefill and decode operations for agentic inference. This approach utilizes a KV cache to link the two stages, reportedly achieving up to a fivefold increase in token throughput in testing. The company aims to scale its daily token processing capacity to between 6 and 10 trillion by the fourth quarter of 2026. AI

IMPACT This architectural split could improve the efficiency and speed of agentic AI systems.

RANK_REASON The item describes a technical architecture detail for inference, not a new model release or core research.

Read on Pandaily →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

SenseTime details SenseCore architecture for agentic inference

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The item describes a technical architecture detail for inference, not a new model release or core research.
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COVERAGE [1]

  1. Pandaily TIER_1 English(EN) · [email protected] (Pandaily) ·

    SenseTime's SenseCore Details Prefill/Decode Split Clusters for Agentic Inference

    At CSDI Summit, SenseCore described domestic Prefill and high-bandwidth Decode linked by KV Cache, about 5x token throughput in one test, and a path from 6 to 10 trillion tokens a day by Q4 2026.

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