There’s a chasm running through the heart of the global tech industry.

On the one hand there are companies like OpenAI, Anthropic, and Google building proprietary (or “closed”) AI models—systems whose training data and source code are accessible only to their owners. On the other are open-weight models, which can be freely accessed and modified by developers. And while the latter has been championed by powerful tech executives like Mark Zuckerberg and Jensen Huang as a counterbalance to corporate greed and a pathway to crowd-sourcing some of the messier problems of AI safety, it still comes with plenty of hazards.

The Chinese AI startup DeepSeek has in many ways become the poster child for the open-weight camp. After it first rocked the foundations of Silicon Valley with the blockbuster release of its R1 model early last year, the company has been on a roll, prompting bitter backlash both from its American rivals and from the Trump administration. On October 17 it released a new model, called V4.1-Flash-1017, which it sold as a cheaper and more efficient version of its flagship AI system. It marks a clear improvement over its predecessors in terms of safety; but there are some critical and concerning gaps that have yet to be fully addressed.

That’s the big takeaway from a new report compiled by researchers at Fangcun AI, an independent AI safety research organization based in Beijing. 8 Flash. It also offers some advice for the growing field of AI safety at a time when models are becoming increasingly “agentic,” or able to autonomously complete more and more complex tasks with less and less human oversight.

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