ElizaOS vs Swarm AI: Who Will Define the Next Generation of Web3 Intelligence Standards?
Recently, the crypto industry has been turbulent, marked by the historically significant theft incident involving Bybit, followed closely by the $50 million theft of web3 “Yu’ebao” inita. Although these incidents have not severely impacted the two projects, the anticipated sell-off of stolen funds and recent struggles have led to a dire market situation, with continuous chatter around the overall market. Conversely, this time presents a great opportunity for serious building, discovering new projects, and accumulating positions at lower prices. The primary narrative for 2024–2025 may revolve around the AI Agent sector, where future new leaders are likely to emerge. Today, I will conduct a simple comparative analysis of two top-tier AI projects from a technical roadmap perspective, aiming to spark further discussion.
I. Technical Showdown: The Underlying Logic of Two Disruptive Architectures
1. ElizaOS: “Lego-style” Expansion with Modular and Open-source Ecosystem
ElizaOS is centered around an open-source modular architecture, allowing developers to freely combine functional plugins (such as TEE privacy computing and multi-chain interaction modules) to build lightweight or enterprise-grade AI agents. Its design philosophy stems from the exploration of basic human-computer interaction through MIT’s ELIZA program in 1966, but it achieves three key breakthroughs through blockchain technology:
– Pluggable Model Integration: Supports plug-and-play integration of large models like GPT-4 and Claude with Web3 protocols (such as DeFi contracts and NFT standards);
– Decentralized Governance: Incentivizes developers to contribute code through the $ELIZA token, with agents in the ecosystem required to allocate 5% of their income to framework maintainers;
– Assurance of Permanence: Smart contracts ensure that agent logic executes indefinitely, allowing for iteration even if the founding team disappears.
A typical case: The AI trading fund AI16ZDAO in the Solana ecosystem is developed based on ElizaOS, with its agents integrating on-chain data from oracle networks and TEE privacy strategies to achieve an annualized yield of over 300% through automated arbitrage.
2. Swarm AI: “Swarm Revolution” of Collective Intelligence and Collaborative Networks
Founded by 20-year-old prodigy Kye Gomez, Swarm AI’s multi-agent collaboration framework redefines the normalization of complex task processing:
– Swarm Nodes: A serverless infrastructure that allows 45 million agents to coordinate simultaneously, addressing hardware dependencies and cost issues;
– Hybrid Flow Model: Combines SSM (State Space Model) and MoE (Mixture of Experts) to achieve superhuman accuracy in scenarios such as medical diagnosis;
– Cross-chain Memory Pool: A decentralized database shared among agents, supporting long-term context tracking and cross-task knowledge reuse.
Market Performance: Despite a 35% short-term drop in the $SWARMS token due to speculative bubbles, its enterprise clients (such as automation in insurance claims for JPMorgan) have validated the technical feasibility.
II. Market Game: Market Capitalization, Community, and Covert Capital Wars
1. Market Capitalization Divergence: Modular Light Assets vs. Heavy Operational Enterprise Services