DeepSeek and Huawei open-source TileLang and Ascend kernels as a CUDA alternative

DeepSeek and Huawei are going after CUDA, NVIDIA's software ecosystem and one of its strongest competitive moats. The release has three parts:

- TileLang, a domain-specific language for writing high-performance kernels on Ascend processors

- DeepGEMM-Ascend, which accelerates matrix multiplication

- DeepEP-Ascend, which handles expert-parallel communication for mixture-of-experts models

The partners also tuned a 128-chip Ascend 950 supernode together.

The approach is pragmatic. NVIDIA's lead depends partly on hardware and partly on more than 15 years of CUDA libraries and developer familiarity. TileLang works at the level of tiles, the blocks of data that kernels operate on, which makes high-performance code easier to write and potentially portable. DeepSeek's own V4.1-Flash is the obvious first workload, and The Next Web describes the release as a real path for Chinese AI stacks away from NVIDIA.

It fits a broader trend this week. Alibaba unveiled its Zhenwu V900 chip, and Chinese labs are building complete domestic stacks as US export controls tighten. Separately, DeepSeek released packaged desktop versions of its DeepSeek Harness app.

Skeptics on community forums question whether a compiler toolchain can realistically erode CUDA's position. The library ecosystem, debugging tools and long-tail operator coverage take years to build, and most Western developers have no Ascend hardware. Watch for third-party projects porting to TileLang, and for whether TileLang targets hardware beyond Ascend.