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AI CURATED HOT STORY · 10/18/2026

NVIDIA Optimizes Kimi K3 Inference Kernel for 1.68x Speedup

1 reports archived1 independent sourcesupdated 10/18/2026, 21:25:18
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NVIDIA achieved a 1.68x inference speedup for the 2.8T-parameter Kimi K3 model on GB300 NVL72 hardware via upstream vLLM optimizations, reaching 423 tok/s/user. The breakthrough relies on a massive 12,000-line Megakernel written in NVIDIA's new Cute DSL, demonstrating the future of AI-assisted generation of advanced compute kernels.

LATEST/NVIDIA achieved a 1.68x inference speedup for the 2.8T-parameter Kimi K3 model on GB300 NVL72 hardware via upstream vLLM optimizations, reaching 423 tok/s/user. The breakthrough relies on a massive 12,000-line Megakernel written in NVIDIA's new Cute DSL, demonstrating the future of AI-assisted generation of advanced compute kernels.

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Total 1 reports · Latest first
  1. IT之家 · 智能时代T2·68 pts
    • Kimi K3 (2.8T params) achieves 423 tok/s/user on GB300 NVL72, a 1.68x improvement over baseline.
    • The optimization centers on a 'Megakernel' decode-specific kernel with 12,000 lines of code, written in NVIDIA's new Cute DSL.
    • This case signals that AI-assisted generation of advanced compute kernels is becoming a key direction for solving LLM inference efficiency bottlenecks.