Within just a week, more than 2 million users have joined the waiting list to access China’s Manus general AI agent. Manus AI is being touted as the “second DeepSeek moment” coming from China. This is when the agent is in closed beta, and can only be accessed via an invitation.
The frenzy has taken hold, with many calling Manus AI a “breakthrough” and a fitting response to OpenAI’s Deep Research agent, especially as China continues to deliver new AI innovations at a cheaper rate. However, the hype surrounding Manus is blown out of proportion, partly because of AI influencers who are making big claims on social media platforms. Here’s why I think Manus AI is a promising start, but not a breakthrough.
Why Manus AI is Not a Breakthrough
The reason DeepSeek was a breakthrough is that it finally replicated OpenAI’s RL method to deliver performance along the lines of o-series reasoning models. Moreover, the DeepSeek team did it on a shoestring budget compared to OpenAI’s training costs. Later on, DeepSeek introduced and open-sourced its GRPO training method, which helped other labs to train frontier-class reasoning models.
These were all fresh innovations, and the DeepSeek team from China achieved them despite the GPU constraints imposed by the US. On the other hand, the Manus general AI agent has clubbed together Anthropic’s Claude 3.5 Sonnet model, and several fine-tuned Qwen models, and relies on the Browser Use open-source project.
While better integration and tooling remain advantages, the real breakthrough lies in pioneering frontier-class models optimized for agentic tasks. Anthropic’s Claude 3.5 Sonnet is one of the best AI models for agentic tasks and coding. In fact, the team behind Manus is internally testing the new Claude 3.7 Sonnet unified model and finds it ‘promising’.
Basically, building capable AI models is still the moat, and it will continue to be in the near future. That said, the Manus AI team must be commended for chaining a lot of tools and environments to complete a task. As I said above, it’s a promising start toward an agentic future.
Manus AI Agent Stumbles
We do not have access to Manus AI, but some X users got early access and they have shared their experiences. Derya Unutmaz, a Biomedical scientist, shared the results on X after running Manus and OpenAI’s Deep Research agent side by side.
He found that Deep Research completed the task in 15 minutes, but Manus ran for 50 minutes and failed to complete the task. He also stated that Manus doesn’t reference sources like Deep Research.
Deep Research finished in under 15 minutes. Unfortunately, Manus AI failed after 50 minutes at step 18/20! 😑 It was performing quite well-I was watching Manus’ output & it seemed excellent. However, running the same prompt a second time is a bit frustrating as it takes too long! https://t.co/bGtmOI65CP
— Derya Unutmaz, MD (@DeryaTR_) March 8, 2025
Similarly, X user teortaxesTex tried the Manus agent and said it’s better at regurgitating stuff like LLMs than performing agentic tasks. Another X user, TheXeophon, also shared his findings after using the Manus agent, which completely failed to mention Nintendo Switch after researching the gaming console market.
In fact, the viral video showing that Manus AI agent automating 50 tasks, turned out to be fake. Yichao ‘Peak’ Ji, the chief scientist of Manus, said, “this video is definitely NOT Manus” with a laughing emoji.
Despite initial stumbles, we must remember that Manus is still in its closed beta phase, and writing it off would be premature. However, it’s equally important to be measured while trying out new AI products. Manus may not be a breakthrough, but it’s an ambitious start in the right direction.
As AI models continue to get better at agentic tasks, new products built on top of them will also see improvement. The Manus AI team has already stated that the agent will be improved significantly before a wider public release. Now, whether it lives up to the hype remains to be seen, but it’s surely a notable development to watch out for.
