DeepSeek Kicks Off ‘Open Source Week’ with Daily AI Code Releases

Chinese AI company DeepSeek has kicked off its ‘Open Source Week,’ promising to release five repositories over the next five days, starting with FlashMLA, an optimized decoding kernel for Hopper GPUs.

DeepSeek, known for its open-weight AI models, announced its ambitious open-source push via social media, emphasizing transparency, community collaboration, and a garage-style innovation mindset. Unlike many AI companies that release only model weights, DeepSeek is opening up parts of its underlying infrastructure, a move that could enhance reproducibility and innovation in AI development.

Day 1 Release: FlashMLA

The first release, FlashMLA, is an efficient decoding kernel for multi-layer attention (MLA) on Hopper GPUs. Designed to improve performance for variable-length sequences, it includes:

• BF16 support for improved precision and efficiency

• Paged KV cache (block size 64) for memory optimization

• Performance benchmarks: 3000 GB/s memory-bound and 580 TFLOPS compute-bound on NVIDIA H800 GPUs

This release suggests a focus on improving AI model efficiency at inference time, though it remains unclear whether DeepSeek will eventually share training code, which is necessary for a fully open-source AI model.

A Challenge to Closed AI Development

DeepSeek’s move contrasts with OpenAI, Google, and Meta, which have released open-weight models but kept their training processes and infrastructure proprietary. By opening up more of its AI stack, DeepSeek is positioning itself as a leader in true AI openness.

The company describes itself as a “tiny team exploring AGI” and emphasizes that these releases are “humble building blocks” that have been tested in production. Their posts suggest a grassroots, community-driven approach, stating:

"No ivory towers—just pure garage-energy and community-driven innovation."

Looking Ahead: What’s Next for Open Source Week?

DeepSeek has not yet revealed what the next four repositories will contain, but the company promises daily releases throughout the week. If future releases include full training code, this could mark one of the most transparent AI releases to date, enabling researchers to reproduce, fine-tune, and modify DeepSeek’s models with complete flexibility.

For now, DeepSeek’s commitment to open AI infrastructure is a significant step in a field where transparency is often limited. The coming days will determine whether this effort is a symbolic gesture or a true game-changer for open-source AI.

What This Means

DeepSeek’s Open Source Week is a significant move in the AI space, reinforcing the growing demand for greater transparency in AI development. While many companies release only model weights, DeepSeek is going further by sharing infrastructure code that powers its models in production.

If future releases include full training code, this could be a major step toward fully open AI, allowing researchers and developers to reproduce, modify, and build on DeepSeek’s work without restrictions. This could also increase competition in the AI industry, challenging companies like OpenAI and Google, which have kept their most powerful models closed-source.

However, the true impact of these releases depends on what’s included in the coming days. Without training code and dataset transparency, DeepSeek’s openness may still be limited. The AI community will be watching closely to see just how far DeepSeek is willing to go in its commitment to open-source AI.

Editor’s Note: This article was created by Alicia Shapiro, CMO of AiNews.com, with writing, image, and idea-generation support from ChatGPT, an AI assistant. However, the final perspective and editorial choices are solely Alicia Shapiro’s. Special thanks to ChatGPT for assistance with research and editorial support in crafting this article.