Standard Kernel builds an AI-driven platform that automatically produces instruction-level, hardware-specialized GPU kernels, replacing static libraries with code precisely tuned to each workload and accelerator. In partner tests on NVIDIA H100 GPUs, the software has delivered 80 % to 4× end-to-end performance gains, occasionally surpassing NVIDIA’s own cuDNN. By operating deep in the systems stack, the company aims to provide day-one peak efficiency for every new chip without months of manual tuning. The Palo Alto–based team includes alumni from MIT, Stanford, UIUC, and SJTU, and has created open-source projects such as KernelBench and Kernel Tree Search. Newly raised capital will fund continued R&D, expansion of deployments with AI-native and enterprise customers, and progress toward adaptive systems software that evolves alongside emerging models and hardware. The company is actively hiring engineers and researchers to advance its kernel generation technology.

Total raised

$20M

Funding rounds

1

Latest round

Seed

Latest activity

Mar 2026