TileLang brings CUDA performance to Python

// 45d agoOPENSOURCE RELEASE

TileLang brings CUDA performance to Python

TileLang is a Python-native DSL built on TVM that enables hand-tuned CUDA performance for complex operations like MoE routing and FP4 quantization. Recently open-sourced as the foundation for DeepSeek’s TileKernels, it supports advanced NVIDIA architectures including Hopper and Blackwell.

// ANALYSIS

TileLang marks a significant shift toward Python-first GPU optimization, proving that accessibility does not have to come at the cost of hardware-level performance. It has been proven at scale by DeepSeek to power critical LLM components like Multi-Head Latent Attention and Mixture-of-Experts routing. With native support for NVIDIA Blackwell and FP4 quantization, it reduces development overhead by allowing complex kernels to be implemented in roughly 80 lines of Python instead of hundreds of lines of CUDA C++.

// TAGS

tilelanggpucudadeepseektvmpythonquantizationmoeml-infrastructureopensource

DISCOVERED

45d ago

2026-04-24

PUBLISHED

45d ago

2026-04-24

RELEVANCE

8/ 10

AUTHOR

Github Awesome

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