Overwhelming Server Demand Forces DeepSeek To Limit Access

Over the past few days, users attempting to access DeepSeek’s AI models have faced significant difficulties. If you’ve tried to access the company’s services but couldn’t, you’re not alone. According to a notification posted on its website, DeepSeek has acknowledged the disruptions, claiming that this is due to overwhelming server demand.

Temporarily limiting access

As a result of this overwhelming server demand, DeepSeek is temporarily limiting access to its AI models. According to the notification, the company says that users will not be able to top up their API credits. If you’ve run out of balance, you’ll have to wait until the company gets back on track. However, if you still have balances left, you can still use them without any issues.

The notice on the company’s website reads, “Due to current server resource constraints, we have temporarily suspended API service recharges to prevent any potential impact on your operations. Existing balances can still be used for calls. We appreciate your understanding!”

DeepSeek has not specified when it expects to fully restore its services, so users just have to wait. However, this is not the first time the company has experienced server issues.

DDoS attacks

When the service first launched, it was met with a series of coordinated DDoS attacks. For those unfamiliar, a DDoS attack disrupts online services by overwhelming them with massive amounts of traffic. Normally a lot of traffic is a good thing, but the goal of these attacks is to overwhelm the servers to the point of breaking. This led to DeepSeek temporarily limiting new user registrations.

That being said, the current problems are more likely due to DeepSeek’s struggle to keep up with demand. The company has faced overwhelming popularity and interest since its launch. While many companies have their own AI models, DeepSeek’s AI model stands out as particularly interesting and disruptive due to its alleged training methods.

DeepSeek trains its AI using the distillation method instead of relying on raw data, as most AI models do. This is more efficient and less resource-intensive. The company claimed that it had only spent $6 million training its AI model. However, a recent report suggests that DeepSeek might have actually spent $1.6 billion, a far cry from its claims of $6 million.

In any case, DeepSeek users will need to remain patient as it works to resolve its server issues. Hopefully, DeepSeek has something long-term in place to prevent issues like this from happening again.