Modular Empire vs Bee Mind: ElizaOS and Swarm AI’s Hundred Billion Track Route War

The confrontation between ElizaOS and Swarm AI is essentially a battle between the spirit of Web3 and AI centralization. When ElizaOS uses modularity to lower the development threshold, the capital behind it is quietly weaving a control network; when Swarm AI holds high the banner of swarm intelligence, technological black-box may spawn new hegemony. Perhaps the real answer lies not in the code, but in whether humans can maintain the bottom line of “proxy sovereignty”

Recently, the crypto industry has been very unstable. There was a history-level Bybit theft incident on the front foot, and $50 million was stolen on the back foot, although the impact on both projects was not so severe. However, the expected selling pressure of stolen funds and the recent struggle have made the market extremely bad and the market chatter. On the contrary, this is a good time to seriously build, explore new projects, and build positions on dips. The biggest narrative of 2024 – 2025 may be the AI Agent track, and future upstarts are likely to be born in this field. Today, from the perspective of technical routes, the author makes a simple comparative analysis of two relatively high-level AI projects to attract others.

1. Technology showdown: The underlying logic of two disruptive architectures

1. ElizaOS: Modularity and Lego-style expansion of the open source ecosystem

ElizaOS withOpen source modular architectureAs the core, developers can freely combine functional plug-ins (such as TEE privacy computing, multi-chain interaction modules) to build lightweight or enterprise-level AI agent6. Its design concept stems from MIT’s ELIZA program’s exploration of basic human-computer interaction in 1966, but three key breakthroughs have been achieved through blockchain:

• Pluggable model integration: Support plug-and-play 4 for large models such as GPT-4 and Claude and Web3 protocols (such as DeFi contracts and NFT standards);

• decentralized governance: Through the token $ELIZA to encourage developers to contribute code, agents within the ecosystem need to allocate 5% of their revenue to framework maintainers 4;

• Eternal guarantee: Smart contracts ensure that the agent logic runs permanently and can be iterated even if the founding team disappears. 6

Typical case: Solana Ecosystem’s AI trading fund AI16ZDAO is developed based on ElizaOS. Its agent integrates data on the oracle chain with TEE privacy policies to achieve automated arbitrage with annualized returns of more than 300%.

2. Swarm AI: The “swarm revolution” of swarm intelligence and collaborative networks

Swarm AI was founded by 20-year-old talented boy Kye Gomez, whoMulti-agent collaboration frameworkRedefined the complex task processing paradigm:

• SwarmNode: Serverless infrastructure, allowing 45 million agents to coordinate simultaneously, solving hardware dependence and cost issues 2;

• mixed flow model: Combine SSM (State Space Model) and MoE (Expert Hybrid) to achieve superhuman accuracy in medical diagnosis and other scenarios 2;

• Cross-chain memory bank: A distributed database shared by agents that supports long-term context tracking and cross-task knowledge reuse2.

Market performance: Although the token $SWARMS plunged 35% in the short term due to speculative bubble1, its enterprise-level customers such as JPMorgan Insurance Claims Automation verified its technical feasibility

2. Market game: market value, community and capital secret war

1. Market value differentiation: modularization light assets versus operational enterprise services

Revenue model:

– elizaOS: Development profit distribution + agreement commission

key differences：

• ElizaOS dependenceViral spread of open source communities, attract developers through the airdrop mechanism (for example, holding $ELIZA will give priority to new proxy tokens)

• Swarm AI focuses onEnterprise payment scenariosHowever, its token economy failed to effectively bind customer growth, resulting in decoupling market value from business.

However, two different routes triggered a conflict:

• a16z tried to integrate ElizaOS into the 50+ projects it invested in, raising concerns about centralization;

• The Swarm community accuses Kye of over-reliance on personal IP and lack of transparency in technical routes

3. Technical long board and fatal flaws

1. ElizaOS: The War of Lightweight and Compatibility

• Advantages:

• Deploy a DeFi arbitrage agent in 5 minutes (integrated with Uniswap and dYdX interfaces);

• Supporting multi-chain environments such as Ethereum, Solana, and Base, the migration cost approaches zero.

• short board

• Communication between modules is inefficient, and complex task delays are as high as minute4;

• Excessive reliance on external large models and weak localization optimization capabilities 6.

2. Swarm AI: A double-edged sword for collaborative networks

• advantages：

• Hundreds of agents collaborate to process insurance claims, and the error rate is 90% lower than that of humans;

• The training cost of the self-developed SSM+MoE model is only 1/20 of that of GPT-4.

• short board：

• Unbalanced task allocation when node networks are congested has led to collective failure of medical diagnosis agents;

• Corporate customers refuse to link up due to data privacy, which conflicts with the vision of Web3;

4. The ultimate showdown: five key battlefields in 2025

1. Developer Mind Battle

• ElizaOS attracts Web2 transformers with “low code + high yield”, and GitHub’s star count exceeds 70004;

• Swarm AI cultivates deep users through hackathons, but its Python SDK learning curve is steep.

2. Privacy computing standard-setting

• ElizaOS integrates TEE plug-in, but the exposed vulnerability can extract smart contract keys;

• Swarm AI developed ZKP verification nodes, sacrificing speed for security, causing community division.

3. On-chain agent supervision game

• The U.S. SEC sued ElizaOS ecosystem project AI16 ZDAO for “manipulating the market” and demanded disclosure of proxy trading logic;

• Swarm AI faces a class action lawsuit over misdiagnosis by a medical agent, and decentralized structure is an excuse for exemption.

4. Low-level public chain alliance competition

• ElizaOS and Solana jointly built a dedicated side chain for AI agents, and TPS has been increased to 100,000 level4;

• Swarm AI selects the Avalanche subnet and customizes virtual machines to optimize swarm scheduling.

5. Red line of life and death: Energy efficiency

• A single ElizaOS agent consumes 0.3 kilowatt-hours per day and is boycotted by environmental organizations;

• Swarm AI reduces energy consumption by 90% through task compression technology, but sacrifices complex task processing capabilities.

5. Industry prediction: 2026 year-end speculation

Scenario 1: ElizaOS unites the world

• Modular framework has become the “default option” for Web3 proxies, with a market value exceeding US$50 billion;

• Cost: Innovation stagnates and developers become ecological tenants 4.

Scenario 2: Swarm AI counterattacks and becomes a god

• Bee swarm collaboration spawns super AI, with autonomous agents taking over 60% of on-chain transactions;

• Risk: An out-of-control agent network triggers financial crisis2.

Scenario 3: The coexistence of two men and the long tail revolution

• ElizaOS monopolizes the simple task market, and Swarm AI adheres to high-end enterprise services;

• New forces (such as federal learning +DAO governance) subvert the existing landscape 6.

Conclusion: Technological utopia or a monopoly tool?

The essence of the confrontation between ElizaOS and Swarm AI isThe spirit of Web3 and AI centralizationThe battle for the route. When ElizaOS uses modularity to lower the development threshold, the capital behind it is quietly weaving a control network; when Swarm AI holds high the banner of swarm intelligence, technological black-box may spawn new hegemony. Perhaps the real answer lies not in the code, but in whether humans can maintain the bottom line of “proxy sovereignty”.

“All technological revolutions were a carnival of idealists in the early stage, and in the later stage they became a chessboard of capital and power.” - -Anonymous AI agent developer@0x_KongKong