AI startup Manus has unveiled Wide Research, a significant enhancement to its agentic platform. This new feature leverages the power of over 100 AI agents working in parallel to tackle large-scale tasks, positioning it as a distinct alternative to the "Deep Research" tools offered by competitors like OpenAI and Google. Manus describes Wide Research as akin to a personal supercomputing cluster, allowing users to manage complex, high-volume research through natural language commands. The feature is initially accessible to Manus Pro subscribers, with a phased rollout planned for other subscription tiers. This development builds upon the considerable attention Manus garnered in March 2025. Initially misidentified as a Chinese venture, its parent company, Butterfly Effect, is now based in Singapore, a move reflecting strategic considerations amidst US-China tech tensions. The launch experienced unprecedented demand, with partner Zhang Tao acknowledging, "we have completely underestimated the level of enthusiasm." Manus's core offering is presented not merely as an AI, but as a "personal cloud computing platform." As detailed in a recent blog post, "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." The foundation of Wide Research lies in each agent operating as a Turing-complete virtual machine. Wide Research fundamentally reimagines AI collaboration through parallel processing and agent-to-agent interaction. Instead of a single agent delving deeply into a task, Manus deploys a swarm of agents that work in unison, effectively granting users control over a personal supercomputing cluster via conversational interface. The objective is to amplify compute power for a single task by a factor of 100, thereby transforming the approach to complex problem-solving. Demonstrations highlight its breadth: in one instance, Wide Research compared 100 different sneakers by assigning each to a concurrent subagent. These agents analyzed individual shoes, collectively producing a sortable matrix in both spreadsheet and webpage formats within minutes. Another example showcased agents generating 50 distinct poster designs simultaneously, consolidating the results into a single ZIP file. The company stresses that “The key to Wide Research isn’t just having more agents — it’s how they collaborate.” Unlike traditional multi-agent systems with fixed, specialized roles, every subagent in Wide Research is a fully functional, general-purpose Manus instance running on its own virtual machine, providing unparalleled flexibility. Wide Research is currently available for users subscribed to the $199/month Pro plan, with subsequent access planned for the Plus ($39/month) and Basic ($19/month) tiers. Manus has labeled the feature as experimental, and while its claims are ambitious, its practical benefits are yet to be empirically proven. This cautious rollout strategy reflects the novelty of its architecture and the significant technical and regulatory challenges it faces. Industry analysts have noted a lack of concrete evidence supporting the "wide" approach, with VentureBeat observing, “while the feature showcases architectural ambition, its practical benefits over simpler methods remain unproven based on the information provided.” Manus has not released performance benchmarks, direct comparisons with single-agent alternatives, or detailed technical specifications regarding subagent collaboration, result merging, or measurable improvements in speed, accuracy, or cost-efficiency. Developing and debugging multi-agent systems is notoriously complex, with developers on other platforms reporting issues such as high token consumption, slow performance, and a lack of execution transparency. Early independent reviews of Manus have pointed to performance inconsistencies, including the generation of simulated data and getting stuck in loops, underscoring the significant technical hurdles Manus must overcome to ensure its agent swarms are reliable and efficient. Furthermore, Manus's focus on autonomous operation has attracted regulatory attention. Shortly after its launch, Tennessee Governor Bill Lee banned Manus from state networks, citing risks of “censorship, propaganda, and bias.” Alabama followed with a similar ban due to perceived security vulnerabilities. This backlash highlights a broader global unease with fully autonomous systems operating without human oversight, which is a core principle of Manus's design. Ultimately, Wide Research represents a significant experiment in scaling AI. As the agentic AI market matures, the distinction between visionary ambition and practical utility will become clearer. The success of Wide Research will depend on its ability to master multi-agent coordination and navigate regulatory skepticism to deliver demonstrable advantages over established, simpler methods.

What is Wide Research and how does it differ from competitors? Wide Research is a new feature from AI startup Manus that uses over 100 AI agents in parallel to tackle large-scale tasks. This approach contrasts with competitors like OpenAI and Google, which Manus describes as offering "Deep Research" tools that focus on a single agent delving deep into a task, rather than a swarm working collaboratively. How does Manus position its AI platform? Manus positions its core product as a "personal cloud computing platform," enabling users to orchestrate complex cloud workloads through natural language by talking to an AI agent. What are some practical examples of Wide Research in action? Wide Research has been demonstrated comparing 100 different sneakers by deploying 100 concurrent subagents, each analyzing one shoe and delivering a sortable matrix. Another example showed agents generating 50 poster designs simultaneously, providing polished assets in a single ZIP file. What are the current access tiers for Wide Research? Wide Research is currently available to Manus Pro subscribers, with plans to gradually roll it out to other subscription tiers. What challenges does Manus face with Wide Research? Manus faces challenges including the lack of empirical evidence for the "wide" approach's benefits, the complexity of multi-agent system development and debugging, potential performance inconsistencies, and regulatory scrutiny regarding autonomous AI systems. What has been the industry and regulatory response to Manus's autonomous AI focus? While the feature showcases architectural ambition, its practical benefits over simpler methods remain unproven. Additionally, regulatory bodies like the state of Tennessee have banned Manus from state networks due to concerns about censorship, propaganda, and bias, with Alabama following suit over security vulnerabilities.

Crypto Market AI's Take

The launch of Manus's Wide Research marks an intriguing development in the burgeoning field of agentic AI. By deploying a swarm of over 100 parallel AI agents, Manus is pushing the boundaries of large-scale task execution, directly challenging the prevailing "deep dive" approach of competitors. This "personal supercomputing cluster" concept, powered by conversational AI, aims to democratize advanced computational capabilities. At Crypto Market AI, we closely monitor advancements in AI and their intersection with financial markets. The ability to scale AI-driven research and analysis in parallel could offer significant advantages for complex market analysis, sentiment tracking, and data aggregation, areas crucial for informed cryptocurrency trading. Our own platform leverages AI for market intelligence, including AI-driven crypto trading bots and AI analysts that provide strategic insights. The collaboration and flexibility offered by Manus's approach could lead to more nuanced and comprehensive market understanding, potentially impacting how traders approach asset analysis and decision-making in the volatile crypto space.

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

Crypto Market AI's Take

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