Manus AI Launches ‘Wide Research,’ Pitting 100-Agent Swarms Against ‘Deep Research‘ from Google and OpenAI

Singapore-based Manus has launched Wide Research, a novel feature for its agentic platform that deploys over 100 AI agents in parallel to tackle large-scale tasks. Announced on July 31, 2025, the system contrasts sharply with the “Deep Research” tools from competitors like OpenAI and Google. Manus frames the new capability as a personal supercomputing cluster, enabling users to orchestrate complex, high-volume research through natural language. The feature is now available to Manus Pro subscribers, with a gradual rollout planned for other tiers, marking a new approach to scaling AI-driven productivity.

From Viral Sensation to Agentic Supercomputer

The launch builds on the significant buzz Manus generated in March 2025. Initially perceived as a Chinese AI venture, its parent company, Butterfly Effect, is now headquartered in Singapore, a strategic response to US-China tech tensions. The debut saw overwhelming demand, with partner Zhang Tao admitting, “we have completely underestimated the level of enthusiasm.” This history of high expectations sets the stage for Wide Research. Manus describes its core product not as an AI but as a “personal cloud computing platform.” In a recent blog post, the company explained its vision, stating, “AI can democratize that power. Behind every Manus session runs a dedicated cloud-based virtual machine, allowing users to orchestrate complex cloud workloads — simply by talking to an agent.” This architecture, where each agent is a Turing-complete virtual machine, is the foundation for its new feature.

How ‘Wide Research’ Reimagines AI Collaboration

At its core, Wide Research is a system for parallel processing and agent-to-agent collaboration. Instead of one agent digging deep, Manus spins up a swarm to work in concert, effectively giving users control of a personal supercomputing cluster just by chatting. The goal is to scale the available compute for a single task by a factor of 100, transforming how complex problems are addressed. The practical applications demonstrate this breadth. In a demo shared by the company, Wide Research was tasked with comparing 100 different sneakers. It instantly deployed 100 concurrent subagents, each assigned to analyze one shoe, and returned a sortable matrix in both spreadsheet and webpage formats within minutes. Another example showcased its creative potential, with agents generating 50 distinct poster designs simultaneously, delivering the polished assets in a single ZIP file. The company emphasizes that “The key to Wide Research isn’t just having more agents — it’s how they collaborate.” This architectural choice is a critical differentiator. Unlike traditional multi-agent systems that rely on predefined, specialized roles like “manager” or “coder,” every subagent in Wide Research is a fully capable, general-purpose Manus instance running on its own virtual machine. This generality is what unlocks the system’s flexibility, ensuring that tasks are not constrained by rigid formats or domains.

A Promising Architecture with Unproven Benefits

Wide Research is available now for users on the $199/month Pro plan, with access for Plus ($39/month) and Basic ($19/month) users to follow. However, the company has positioned the feature as experimental, and despite the ambitious claims, its practical benefits remain unproven. This cautious rollout reflects both the novelty of the architecture and the significant technical and regulatory hurdles the platform faces. Industry analysis has been quick to point out the lack of empirical evidence supporting the “wide” approach. As noted by VentureBeat, “while the feature showcases architectural ambition, its practical benefits over simpler methods remain unproven based on the information provided.” The company has not released performance benchmarks, direct comparisons to single-agent alternatives, or technical explanations detailing how subagents collaborate, how results are merged, or whether the system offers measurable advantages in speed, accuracy, or cost-efficiency. These are not trivial hurdles. The broader tech community has a mixed record with multi-agent systems, which are notoriously complex to develop and debug. Developers working with other platforms have reported challenges with high token consumption, slow performance, and a lack of visibility into execution. Early independent reviews of Manus itself noted performance inconsistencies, including generating simulated data or getting stuck in loops. These issues highlight the steep technical climb Manus faces in ensuring its agent swarms are both reliable and efficient. Furthermore, the company’s focus on autonomous operation has attracted significant regulatory scrutiny since its debut. Shortly after its initial launch, Tennessee Governor Bill Lee banned Manus from state networks, citing risks of “censorship, propaganda, and bias.” Alabama soon followed with a similar prohibition over security vulnerabilities. This government pushback reflects a global unease with fully autonomous systems that operate without a human-in-the-loop, a core design principle of the Manus platform. Ultimately, Wide Research represents a bold experiment in scaling AI. As the agentic AI market matures, the line between ambitious vision and practical utility becomes sharper. Its success will depend entirely on whether the architectural vision can overcome the well-documented challenges of multi-agent coordination and navigate a skeptical regulatory environment to deliver tangible advantages over simpler, more established methods.

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Frequently Asked Questions (FAQ)

What is Manus AI's Wide Research feature?

Wide Research is a new feature from Manus AI that allows users to deploy over 100 AI agents in parallel to tackle large-scale tasks, acting like a personal supercomputing cluster.

How does Wide Research differ from competitors like Google and OpenAI?

While competitors focus on "Deep Research" with single or fewer agents, Wide Research emphasizes parallel processing and agent-to-agent collaboration with a swarm of over 100 agents to handle high-volume research tasks simultaneously.

What are the practical applications of Wide Research?

Practical applications include quickly comparing numerous items (like 100 sneakers), generating diverse creative outputs (like 50 poster designs), and scaling complex data analysis by leveraging the power of many agents working in concert.

What are the challenges or limitations of Wide Research?

The article notes that the practical benefits of Wide Research are currently unproven, with a lack of empirical evidence and performance benchmarks. The complexity and reliability of multi-agent systems, along with regulatory scrutiny of autonomous AI, are also noted challenges.

What is the pricing for Manus AI's Wide Research feature?

Wide Research is currently available to Manus Pro subscribers ($199/month), with plans to roll it out to other subscription tiers in the future.

Crypto Market AI's Take

The launch of Manus AI's Wide Research highlights a significant shift in how AI is being applied to complex research and analysis tasks. By leveraging a "swarm" of over 100 AI agents, Manus is aiming to provide a vastly more scalable and efficient approach compared to traditional single-agent models. This move mirrors the growing trend in the AI landscape towards more distributed and collaborative AI systems, a concept we explore in our articles on AI agents and their burgeoning role in various industries. The ability to orchestrate such a large number of agents for tasks like large-scale data comparison or generative design suggests a powerful new paradigm for productivity. However, as the article points out, the practical efficacy and reliability of such complex systems are still under scrutiny. This echoes the broader challenges and opportunities within the AI and crypto intersection, where innovation often outpaces established validation. We believe that advancements like Wide Research will increasingly influence how market analysis and data processing are conducted, potentially leading to more sophisticated and automated strategies in the crypto space.

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Source: Manus AI Launches ‘Wide Research,’ Pitting 100-Agent Swarms Against ‘Deep Research‘ from Google and OpenAI