The world's most powerful general agent II-Agent is released! Crush Manus and Genspark
The launch of II-Agent marks a new milestone in the field of AI. Its open source features and excellent performance have shocked the industry.
Core content:
1. II-Agent's breakthrough performance in the GAIA benchmark
2. II-Agent's open source framework and powerful functions
3. Comparative advantages with Manus and GenSpark AI
The biggest bombshell of open source AI Agent is here!
The Intelligent Internet (II) team has just released what may be the world's most powerful general AI agent , and it's completely open source!
This may not be ordinary open source, but a real open source cannon .
II-Agent achieved an amazing score of 75.57% on Meta's GAIA benchmark , far surpassing all publicly available models and taking a big step towards the human level (92%).
This has really made the closed-source Manus and GenSpark AI anxious!
GAIA
GAIA is a new benchmark released by Meta that specifically evaluates the capabilities of AI assistants in handling a variety of real-world scenarios, including multimodal processing , tool usage , and web search .
This benchmark is very challenging.
According to Meta’s paper, an average human can achieve 92% accuracy on this test , while GPT-4 equipped with a plug-in can only achieve 15%.
This huge gap shows that although current AI models have surpassed humans in professional fields such as law and chemistry, AI still has a long way to go in some tasks that are simple for humans.
II-Agent's score of 75.57% narrowed the gap !
II-Agent: A powerful and extensible open source framework
So, what exactly is this II-Agent?
II-Agent is a fully open source intelligent assistant framework designed to improve workflow efficiency in various fields. It not only works out of the box, but can also be easily adapted and extended.
The II team's mission is to " increase human intelligence ", and they believe that:
2025 is the year of agents. For things to really matter, their agents must be open, transparent, and usable.
It seems that the II team is not just satisfied with releasing a single agent, they are building a broader system because they believe that the future will be an era where " agent groups work for all of us ."
Comparison with Manus and GenSpark AI
If you don’t know this field yet, you need to know:
Manus is an advanced autonomous AI agent launched by Chinese startup Monica (Butterfly Effect AI) in March 2025. It is capable of handling complex tasks, integrating multiple tools, and scoring around 65% on the GAIA benchmark.
GenSpark AI is an innovative AI agent engine founded by former Baidu executives. It reimagines traditional search methods and uses a multi-agent framework to generate customized real-time "Sparkpages" for user queries.
While both of these are industry-leading products, they are closed source .
The emergence of II-Agent brings a completely open source option with performance that surpasses them!
II-Agent's Core Capabilities
II-Agent is a comprehensive agent that can do everything :
Research and fact-checking : multi-step web search, source triangulation, structured note-taking, quick summarization
Content generation : blog and article drafts, lesson plans, creative essays, technical manuals, website creation
Data analysis and visualization : cleaning, statistics, trend detection, charting, automatic report generation
Software Development : Code synthesis, refactoring, debugging, test writing, and step-by-step tutorials across multiple languages
Workflow automation : script generation, browser automation, file management, process optimization
Problem Solving : Decomposition, exploration of alternative paths, step-by-step instructions, troubleshooting
K(@K_to_Macro) asked: “Wait, this is the MIT license?”
The answer is:
Technical Details: How Does It Work?
The II-Agent system is built around Anthropic's Claude model and provides:
CLI interface, interact directly on the command line
A WebSocket-based server that powers modern React frontends
Integration with Google Cloud’s Vertex AI for API access to Anthropic models
The core methods include:
Core Agent Architecture and LLM Interaction
Dynamic system prompts Comprehensive interaction history management Smart context management Planning and reflection
Structured Reasoning Problem decomposition and sequential thinking Hypothesis Formulation and Testing Execution capability
File system operations Command line execution Network interaction and browser automation
These technical details allow II-Agent to think and work like humans , rather than simply responding to instructions.
