DeepSeek open-sources TileKernels GPU library

// 45d agoOPENSOURCE RELEASE

DeepSeek open-sources TileKernels GPU library

DeepSeek's TileKernels is a library of high-performance GPU operators for LLM training and inference, written in the Python-based TileLang DSL. It features production-ready kernels for MoE routing, multi-precision quantization, and MLA, specifically optimized for NVIDIA Hopper and Blackwell architectures.

// ANALYSIS

DeepSeek is systematically replacing the traditional CUDA C++ and Triton stack with their own automated compiler DSL to achieve hardware-limit performance.

–TileLang allows DeepSeek to implement complex kernels like MLA in ~80 lines of Python while matching the speed of thousands of lines of CUTLASS C++.
–The library provides first-class support for FP4 and FP8 quantization, signaling a shift towards aggressive multi-precision training on next-gen hardware.
–By open-sourcing these internal kernels, DeepSeek is positioning TileLang as a serious competitor to OpenAI's Triton for custom GPU operator development.
–The focus on Hopper (SM90) and Blackwell (SM100) indicates these kernels are built for the absolute cutting edge of AI infrastructure.

// TAGS

gputilelangdeepseekllmopen-sourceinfrastructurecudahopperblackwell

DISCOVERED

45d ago

2026-04-24

PUBLISHED

45d ago

2026-04-24

RELEVANCE

9/ 10

AUTHOR

Github Awesome

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