T-Head Opens Source for AI Software Stack: Domestic Chip Competition Shifts from Hardware Specs to Ecosystem Co-building

At the Apsara Conference on September 22, Alibaba Group CEO Eddie Wu introduced the new generation Zhenwu V900 AI chip, stating its performance is three times that of the M890. However, for customers considering switching to Zhenwu, beyond the 'hard power' of computing capacity, the more critical issue is whether their existing code, tools, and development experience can be smoothly migrated. Beyond the chip itself, the 'soft power' of the software ecosystem equally determines customer choices.

One day later, on September 23, T-Head announced the latest open-source progress of its AI software stack, T-Head SAIL, further expanding the scope of openness in framework adaptation, acceleration libraries, toolchains, and communication libraries. T-Head likens the AI chip to an engine, while the software stack acts as the 'transmission + drivetrain + driving system.' The newly opened projects include PyTorch-for-sail framework adaptation, sailify source code migration tool, Triton-for-sail kernel development tool, and compute acceleration projects such as DeepGEMM-for-sail and FlashAttention-for-sail.

This initiative addresses three key problems developers face in actual business operations. First is migration cost: Lu Shenghua, Senior Director of Software Ecosystem at T-Head Semiconductor, stated, 'The biggest demand, from a business perspective, is how large the migration cost is.' By opening up migration tools, developers can continue using familiar model development methods, preserving past accumulations as much as possible. Second is performance optimization: if efficiency drops significantly after switching chips, it is hard for businesses to accept. Open-sourcing acceleration projects allows developers not only to download ready-made tools but also to directly view implementation details, locate bottlenecks, and optimize based on their own business loads. Third is Day 0 support: being able to test new models on the computing platform on the day of release has become an expectation. T-Head has already provided 39 quantized models on ModelScope, with cumulative downloads exceeding 348,000.