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Genspark super-agent: the rise of next-generation AI assistants and how it compares to Manus AI

Genspark super-agent: the rise of next-generation AI assistants and how it compares to Manus AI
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Autonomous AI agents are taking centre stage in 2025. No longer limited to basic automation or scripted interactions, these agents now operate independently, make decisions, and handle complex workflows across diverse domains. Among the frontrunners in this shift is Genspark Super Agent—an AI assistant designed to perform high-level tasks with minimal human input, combining reasoning, execution, and adaptability in one system.

This blog unpacks the architecture and features that power Genspark, examines how it’s being used in the real world, and provides a side-by-side comparison with Manus AI, another well-known autonomous agent. As AI continues to expand its role across industries, understanding what separates these agents—and where they fit into practical business and individual workflows—is more relevant than ever.

What is Genspark super agent?

Genspark Super Agent, developed by Palo Alto-based startup MainFunc and released in early 2025, marks a major advancement in autonomous AI technology. Built to think, plan, act, and use tools independently, it handles complex, real-world tasks with minimal user input.

What sets Genspark apart from traditional AI assistants is its ability to go beyond basic commands. Instead of simply responding to prompts, it orchestrates multi-step workflows—drawing from multiple data sources, using external tools, and adapting its actions based on evolving needs. 

Whether it’s planning an international trip, conducting in-depth market research, or producing multimedia content, Genspark functions more like an intelligent executive assistant than a chatbot. It not only executes tasks but also provides clear visibility into how and why it makes decisions—bringing transparency to every action it takes.

The technical architecture behind Genspark super agent

At the core of Genspark’s capabilities lies its innovative “Mixture-of-Agents” architecture, which distinguishes it from many other AI systems in the market.

GAIA benchmark

Mixture-of-agents design

Genspark Super Agent integrates nine distinct large language models (LLMs), over 80 in-house tools, and more than ten curated datasets MarkTechPost1. This design enables the system to intelligently route each task to the optimal model based on complexity, speed, and accuracy requirements.

The architecture allows Genspark to:

  1. Dynamically select models: Unlike systems that rely on a single model for all tasks, Genspark chooses the most appropriate model for each specific requirement, improving both performance and efficiency.
  2. Maintain rich context: The system employs the Model Context Protocol (MCP) to carry detailed tool and memory contexts across multiple steps, ensuring coherence throughout complex tasks VentureBeat2.
  3. Direct API integration: Rather than being limited to web-based interactions, Genspark directly calls APIs for structured and rapid data retrieval, significantly reducing execution time and potential errors.
  4. Transparent reasoning: The system visually displays its thought process, showing which tools it invokes and why, providing users with insight into its decision-making.

This architectural approach has enabled Genspark to achieve impressive benchmark results, scoring 87.8% on the GAIA benchmark, which evaluates AI agents on real-world task automation VentureBeat2.

Key features of Genspark super agent

Genspark Super Agent offers a comprehensive suite of features designed to handle diverse tasks across multiple domains:

Key features of Genspark super agent

1. Autonomous task planning and execution

The system can efficiently plan and execute multi-step tasks with minimal supervision. It breaks down complex requests into manageable steps, selects appropriate tools, and executes each step in sequence, maintaining context throughout the process.

2. Real-time voice automation

One of Genspark’s most distinctive features is its ability to perform actual phone calls using AI-generated voices. This enables real-world interactions like restaurant reservations, appointment scheduling, or information inquiries MarkTechPost1.

3. Dynamic content generation

Genspark excels at creating high-quality multimedia content, including:

  • Videos (including animated content)
  • Websites
  • Professional presentations
  • Interactive media

This capability allows for the rapid production of professional and engaging content with minimal user input Medium3.

4. Live data integration and research

The agent can conduct comprehensive research by gathering, analyzing, and synthesizing information from multiple online and internal sources. It produces accurate, citation-rich research reports valuable for market analyses, competitive research, and academic purposes MarkTechPost1.

5. User-friendly interface

Genspark offers an intuitive, conversation-based interface that requires no technical setup. Users can begin experimenting with the platform immediately without providing personal credentials, making it accessible to users of varying technical expertise VentureBeat2.

6. Generous free tier

Unlike many competitors, Genspark offers a free tier with 200 daily credits, making it highly accessible for individuals and small businesses wanting to explore AI agent capabilities MarkTechPost1.

Genspark super agent

Real-world applications of Genspark super agent

Genspark Super Agent’s versatility makes it applicable across numerous use cases:

Automated trip planning

The system can plan comprehensive trips by gathering real-time data on accommodations, weather, attractions, and events. For example, a simple command like “Plan a weekend trip to San Diego” results in a complete itinerary with hotel recommendations, activity suggestions, and even restaurant reservations through its voice-calling feature MarkTechPost1.

In a demonstration, Genspark’s agent planned a five-day San Diego trip, calculated walking distances between attractions, mapped public transit options, and used voice-calling to book restaurants while accounting for food allergies and seating preferences VentureBeat2.

Creative content production

Genspark can create sophisticated multimedia content autonomously. It has demonstrated the ability to:

  • Generate cooking video reels with recipe steps, video scenes, and audio overlays
  • Produce South Park-style animated episodes about current events
  • Create professional presentations and interactive websites

These capabilities significantly reduce the time and resources needed for content creation VentureBeat2.

Market research and analysis

The agent excels at gathering and synthesizing information for market research and competitive analysis. It can research industry trends, identify key players, analyze growth areas, and compile comprehensive reports with proper citations Medium4.

Data analysis and visualization

Genspark can process large datasets, identify patterns and trends, and create interactive visualizations to help users understand complex information intuitively.

Data analysis and visualization

Introducing Manus AI: a Leading competitor

To understand Genspark Super Agent’s position in the market, it’s essential to compare it with one of its primary competitors, Manus AI.

Manus AI, developed by Chinese startup Monica and launched in early 2025, quickly gained recognition for its strong performance across a wide range of autonomous tasks. Designed to operate with minimal oversight, Manus AI can independently execute complex, multi-domain workflows—making it a serious contender in the autonomous agent space.

Its integration with platforms like Hugging Face has further extended its capabilities, allowing it to tap into powerful open-source models and tools. From automating research processes to managing business operations, Manus AI is positioned as a versatile and capable system for both enterprise and individual use.

Key features of Manus AI

Manus AI offers several powerful capabilities:

  1. Autonomous task execution: Manus can independently handle complex workflows including report writing, spreadsheet creation, data analysis, and content generation Hugging Face5.
  2. Multi-Modal processing: The system processes and generates multiple types of data, including text, images, and code Hugging Face5.
  3. Advanced tool integration: Manus integrates with external tools such as web browsers, code editors, and database management systems Hugging Face5.
  4. Code execution and deployment: It can write, test, and deploy code across more than 20 programming languages and frameworks, including setting up websites and hosting services AI Fire6.
  5. File system management: Manus can navigate websites, extract data, interact with web elements, and manage files for document-based workflows AI Fire6.
Manus AI

The technical architecture of Manus AI

Manus AI utilizes a multi-agent architecture where various specialized sub-agents work together. It primarily integrates two large language models, including Anthropic’s Claude, and supplements these with specialized tools and capabilities of AI Fire6.

Genspark Super Agent vs. Manus AI

Category Genspark Super Agent Manus AI
Technical Architecture Uses 9 LLMs, 80+ tools, 10+ proprietary datasets; dynamic Mixture-of-Agents model routing; fast API access. Great for flexible, general-purpose tasks. Uses 2 core models with a multi-agent architecture focused on technical system integration and developer tools. Better for dev-heavy workflows.
User Interface Intuitive, zero-setup UI with no waitlist. Designed for accessibility and non-technical users. Shows its thought process visually. Technical interface requiring a waitlist. Tailored for power users comfortable with system-level customization.
Unique Features Real-time phone calls, video generation, trip planning with real-world integrations, creative content tools. Deep technical tooling: advanced code execution in 20+ languages, file system management, and data visualization.
Performance (GAIA Benchmark) Scores 87.8%. Excels at real-world automation, planning, and general task execution. Scores 86%. Performs strongly on complex technical and data-centric tasks.
Pricing Free tier with 200 daily credits; instant access. Premium tier pricing is not publicly detailed but is reportedly competitive. $39/month (Starter) and $199/month (Pro). High credit consumption (600+ per complex task). Waitlist required.
Strengths Broader model selection, real-world interaction (e.g., calls), creative/multimedia outputs, user-friendly for beginners. Ideal for software developers: strong code execution, deep system integration, and technical documentation.
Limitations Less ideal for specialized dev work, newer to market with less community feedback, vague premium pricing. High cost, occasional server issues, less intuitive UI, lacks native video generation or voice tools.

Task performance comparison

Task Genspark Super Agent Manus AI
Trip Planning Fully autonomous: books via phone calls, calculates routes, handles dietary needs. End-to-end automation. Generates written itineraries and research but lacks automation or real-world booking tools.
Content Creation Excels in video, animation, websites, and interactive media. Very little guidance is needed. Strong for text and static visuals, but lacks creative/multimedia capabilities.
Research Balances citation-rich general and technical research, presented in easy-to-understand formats. Better for deep, technical, and domain-specific analysis with detailed reports.
Technical Tasks Handles general coding and app creation with accessible interfaces. Not aimed at experts. Built for developers. Handles advanced programming, system tasks, and deployment workflows.

Conclusion

The rise of autonomous AI agents like Genspark Super Agent and Manus AI reflects a broader shift in how businesses and platforms approach complex task execution. In 2025, AI agents are no longer experiments—they’re becoming operational. According to industry data, the global AI agent market is projected to hit $7.63 billion this year, with a 45.8% growth rate, driven by demand for task automation and smart decision systems. Major enterprises like Deloitte have already seen over 75% of their UK audit staff adopt internal AI agents for summarizing content, writing code, and performing research.

This trend extends into platforms like Drupal, where AI is moving beyond simple enhancements to become part of the core content workflow. Modules like OpenAI and Augmentor are actively being used to generate content, rewrite copy, and automate image creation. Discussions from DrupalCon Atlanta 2025 make it clear: AI isn’t just an add-on—it’s shaping the future of editorial and publishing systems.

Genspark and Manus represent two paths in this shift: accessible, real-world interaction vs. developer-grade autonomy. But both are part of the same direction—toward agents that don't just assist, but fully handle planning, creation, analysis, and execution. And as Drupal and other systems become agent-ready, we’re entering a phase where much of our work—whether technical, creative, or operational—starts with a single command to an AI agent.

https://www.youtube.com/live/NvsIsDv5UzY

https://www.youtube.com/live/IilRuxCr3Ho 

https://www.youtube.com/live/XIlP6oYTs8w


Written by
Editor
Ananya Rakhecha
Tech Advocate