What Is Manus Wide Research?
Manus Wide Research is a breakthrough AI research feature—launched on July 31, 2025—by Manus (now headquartered in Singapore). It unleashes hundreds of fully capable AI agents (e.g. 100+), each acting as a general-purpose instance, working in parallel to tackle large-scale tasks like researching 100 sneakers or generating 50 poster designs in minutes rather than hours.
Unlike OpenAI’s Deep Research or Google’s Deep Think, which rely on a single agent processing data sequentially, Manus’s approach enables modular, scalable exploration via agent swarms, radically speeding up both research and creative ideation workflows.
From Agent Assistant to Agent Swarm: Background & Context
Manus: Rapid Rise of a General‑Purpose AI Agent
- Manus first gained attention in early 2025 as one of the earliest fully autonomous AI agents, capable of reasoning, tool usage, code execution, and real-world task management—all via a dedicated cloud‑based VM interface.
- Manus secured $75M in funding led by Benchmark, with Tencent and ZhenFund participating, prompting a relocation of its headquarters from China to Singapore, Tokyo, and San Mateo.
Why Wide Research Is a Strategic Step
While Deep Research agents excel at depth, there’s growing demand to handle volume—e.g. compare hundreds of entities rapidly. Wide Research was Manus’s answer: a system that distributes tasks across dozens or hundreds of equal-level agents, breaking traditional single-agent execution bottlenecks.
How Wide Research Works: Architecture & Parallelism
Agent‑Cluster Collaboration & Virtualization
- Wide Research runs each agent on a dedicated virtual machine, enabling parallelism and isolation. Once a user assigns a task, agents proceed asynchronously, returning structured outputs that are aggregated in formats like spreadsheets or web pages.
- Agents use a proprietary protocol for sub-agent communication, decomposing large tasks into subtasks and merging results—without predefined agent roles like “manager” or “designer”.
Key System Features
- Parallel Processing: Any scale—from dozens to hundreds of agents—active per task.
- General‑Purpose “Homogeneous” Agents: Every agent is a miniature copy of the main Manus instance, able to pivot across tasks flexibly.
- Asynchronous Task Execution: Users can submit a task and return later for results, freeing them to move on to new prompts.
- Multi‑domain, Multi‑modal Support: Agents can research text, analyze images, generate creative deliverables—all from user prompts.
Wide Research in Action: Demos and Real‑World Effects
- Sneaker Comparison Demo: In a public demo by co-founder Yichao “Peak” Ji, Wide Research spun up exactly 100 agents—each assigned a different sneaker model. In under 5 minutes, it produced a sortable matrix comparing design, price, availability, and categories—far faster than sequential Deep Research could.
- Creative Poster Generation: Another demo requested “50 poster designs” across different visual styles. Wide Research generated all 50 assets simultaneously and packaged them in a downloadable ZIP—ideal for design teams or marketing agencies.
- According to social media reach, the sneaker demo received thousands of views and questions, signaling wide public interest in high‑scale agent capabilities.
Wide Research vs. Deep Research & Deep Think
| Feature | Wide Research (Manus) | Deep Research / Deep Think |
| Agents per task | Dozens to hundreds of homogeneous agents in parallel | One specialist agent working in series |
| Best for | High-volume tasks: compare 100 MBA programs, stock trends | Deep, nuanced tasks: white‑paper summarizations |
| Speed | Minutes | Often tens of minutes |
| Scalability | Scales linearly across items | Limited by sequential throughput |
| Flexibility | Fully prompt‑driven, creative, cross-domain | Structured prompts, domain constrained |
| Resource usage | High; dependent on agent count | Lower per-task but slower |
| Proven benchmarks | Lacking quantitative head‑to‑head results | Verified performance on GAIA, HLE benchmarks |
It’s strength is speed and breadth, while Deep Research shines in depth and reasoning precision. Manus claims Wide Research “outperforms Deep Research” in terms of speed and variety; however, it has yet to release direct comparative benchmarks or accuracy metrics to validate those claims independently.
Notably, Google’s Google’s Deep Think also explores parallel reasoning with agent-like architecture designed to solve harder problems (e.g., math olympiads), but its public roll-out is still limited and less generalized than Manus’s system, which is available via subscription to end users.
Use Cases: Where Wide Research Unlocks Value
Market Research & Product Analysis
Large consumer brands can instantly compare 100+ product SKUs, gathering price, review sentiment, and feature data in parallel.
Academic & Competitor Scanning
Researchers tasked with analyzing top MBA programs or universities worldwide can rely on agent clusters to extract curricula, tuition, rankings—to assemble a comparative dossier in minutes.
Creative Agencies & Designers
Agencies can generate multiple poster mockups or content variations infinitely, designing campaigns at volume with rapid feedback loops.
Investor Intelligence
Analyzing trends across 1,000 stocks—tracking performance, metrics, market news—can be automated at scale with structured results output for dashboards or spreadsheets.
Social & Trend Surveillance
Social listening: deploy agents to review niche subreddits or product forums across 100+ threads simultaneously, surfacing sentiment shifts or meme trends.
Accessibility & Pricing: Getting Hands on Wide Research
Wide Research is currently available only to users on the Manus Pro plan (~$199/month) and will gradually roll out to Plus ($39/month) and Basic ($19/month) tiers in the coming weeks.
- Free tier: $0/month, offers 300 daily refresh credits and allows one concurrent task, but no access to Wide Research.
- Basic at $19/month: 2 concurrent tasks, early access to image/video generation—not Wide.
- Plus at $39/month: 3 concurrent tasks, but Wide Research still locked.
- Pro ($199/month): Up to 10 concurrent Wide Research operations, 19,900+ credits, priority beta access, and advanced agent tooling.
A 17% annual discount is offered for pre-paid yearly subscriptions.
Trade‑offs and Limitations
Experimental System: Manus acknowledges Wide Research is still in an experimental phase with known limitations like submerged costs, occasional agent coordination quirks, and limited transparency in sub-agent protocols.
Coordination Complexity: With 100+ agents working independently, consistency across results depends on Manus’s underlying aggregation protocol—error handling and result merging are still under refinement.
Higher Cost per Task: Spawning hundreds of agents can inflate infrastructure use. While Pro includes generous credits, high-volume users may still hit limits.
Lack of Public Benchmarks: Manus has not released GAIA or HLE benchmarks for Wide Research, nor direct comparisons to OpenAI or DeepThink—making its claims largely qualitative.
Regional Access: Manus no longer provides services in mainland China after relocating its ops to Singapore and California, which may impact some users and IP considerations .
Getting Started: How to Use Wide Research Today
Create a Manus account and sign up for Pro or wait for rollout to Plus tier.
Use Discord‑style UX or browser UI to issue prompts like:
- “Compare 100 sneakers on design, reviews, price.”
- “Generate 50 posters in different styles around climate change.”
Receive visual output: spreadsheet, sortable matrix, ZIP file with PDFs/PNGs, or webpage reports.
Customize, Filter, or Remix sample agents to adjust tone, data fields, or creative style.
Automate via API: Manus supports developer workflows integrating API testing tools (e.g. Apidog), enabling robust pipelines for research automation and delivery documentation.
Why Manus Wide Research Matters
- Democratizes high-volume research: Individuals or small teams can tackle huge comparison tasks once reserved for large operations.
- Accelerates insight generation: Discover patterns faster, enabling rapid decision-making in marketing, research, or design.
- New paradigm for autonomic AI workflows: The agent‑swarm model tests the future of AI as elastic, cloud-first, self-coordinating systems, rather than isolated chatbots.
- Signals Tech Trends: As Google and OpenAI pioneer multi-agent AI, Manus is positioning itself at the forefront—driving mass adoption and seamless tool-chain integration.
Final Takeway
Manus Wide Research marks an ambitious step forward in autonomous agent architectures. By decentralizing task execution to hundreds of identical agents working concurrently, it reimagines how large-scale data gathering, creative output, and multi-task projects can be completed by a single user with a prompt.
While it currently requires a Pro subscription and lacks benchmark transparency, its high-speed capabilities offer a glimpse into AI’s next frontier: scale without sacrificing flexibility. For anyone seeking to streamline high-volume research, automate parallel tasks, or prototype ideas at speed—Wide Research is a powerful tool to explore.
FAQs
Is Manus Wide Research free to use?
Only the viewing interface is free. Creating tasks with Wide Research requires the Pro plan ($199/month). Basic and Plus tiers will gain access later, but are not yet enabled for Wide Research.
Can I do Wide Research in the free tier?
No. Free tier users are limited to one simple query and cannot access the high-volume capabilities of Wide Research.
What’s the difference between Wide Research and Wide Research in plus/basic?
Only Pro users can spin up more than 10 concurrent high-scale tasks. Plus and Basic users have fewer credits and limited concurrency until full rollout.
Does Wide Research work in languages other than English?
Wide Research supports natural language prompts and can process multilingual queries, but complex extraction may work best in English due to the underlying LLM tuning.
How does it compare to OpenAI’s Deep Research or Google Deep Think?
Wide Research radically differs by using multiple agents in parallel, enabling tasks that involve hundreds of items. Deep Research and Deep Think process data sequentially via a single specialized agent, emphasizing reasoning depth over scale.
