Chinese AI lab DeepSeek released DeepGEMM, a game-changing tool for AI speed. It’s an FP8 GEMM library that supercharges their V3 and R1 models. Fans are cheering. Developers are diving in. This feels big.
DeepGEMM tackles a big problem. It speeds up matrix math for AI training and use. It works on NVIDIA’s Hopper GPUs, hitting 1,350+ FP8 TFLOPS that’s lightning fast. It supports dense and MoE layouts, cutting memory limits and boosting efficiency. Posts on X call it a “breakthrough” for deep learning. It’s free, open-source, and has only 300 lines of core code simple yet powerful.
This launch kicks off Day 3 of DeepSeek’s “Open-Source Week.” Last week, they promised five new repos. FlashMLA came first, speeding up AI on NVIDIA chips. Now DeepGEMM follows. Rumor has it, that more updates are coming. The team’s racing to share. They’re still riding the wave from R1’s January splash. That model shocked the world, outperforming OpenAI’s o1 at a fraction of the cost.
But there’s buzz beyond tech. Chinese firms like Tencent, Alibaba, and ByteDance are using DeepSeek’s tools, driving NVIDIA’s H20 chip orders sky-high. Yet, U.S. worries linger. Officials are probing if DeepSeek accessed fancy NVIDIA chips through backdoors. That tension echoes last month’s $1 trillion market drop tied to DeepSeek’s rise. Trump’s team might tighten the rules on chip sales in China.
For Liang Wenfeng and his crew, this is personal. They’re small but scrappy. DeepGEMM shows its heart for open innovation. It’s not just code. It’s a mission to make AI faster, cheaper, and global. As the sun sets in Hangzhou, the AI world watches, hopeful and curious. What’s next for DeepSeek? Stay tuned.
I’m David Paul, a news writer at DeepSeek Insider, where I cover the latest developments in artificial intelligence, large language models (LLMs), and emerging AI tools in the market. With a keen interest in these cutting-edge technologies, I deliver insightful and timely updates to keep our audience informed and engaged.