Source: Blockchain Knight

In early 2025, the Crypto industry ushered in a wave of social platform automation , and the AI ​​proxy framework is undoubtedly the key driver behind the scenes. From automatically managing social content to generating personalized NFTs, these technologies are redefining how users interact with blockchain.

This article will conduct in-depth discussion on how six major AI proxy frameworks - ElizaOS, G.A.M.E, ARC, ZEREBRO, REI and Swarms, relying on their unique technical advantages to this Taking the lead in the Crypto industry boom, and what are the latest developments of these teams after experiencing the hype boom, and where will they go in the future?

ElizaOS is an open source framework designed to create, Deploy and manage autonomous AI agents. Built with TypeScript, it provides a modular and scalable platform that enables developers to create intelligent agents that interact on multiple platforms such as Discord, Twitter, Telegram, while maintaining consistent personality and knowledge.

Technical advantages:

TypeScript-based design reduces the developer's learning curve, Compared with frameworks that use Rust (such as ARC) or Python (such as ZEREBRO), it is easier to get started quickly, with higher ecological maturity and developer adoption rates.

Github stars:

14.7K

https://github.com/elizaOS/eliza

Latest developments:

Core functions and design concept updates: The documents and white papers released in January this year emphasize the five core components of ElizaOS: agents, character files, providers, and actions And commentsEvaluators, these form a powerful, controllable framework tailored for Web3.

MultiversX AI Agent Toolkit: MultiversX announced the launch of the ElizaOS-based AI Agent Toolkit through X in mid-to-early February 2025. This open source toolkit allows developers to build custom AI agents in minutes, supporting over 250 models, including the new DeepSeek model.

Integration with Sei Network: ElizaOS recently integrated with Sei Network, which is known as one of the fastest blockchains, allowing AI agents to be able to use Sei Run independently on the site and perform tasks such as Crypto transactions and asset management.

ElizaOS v0.25.8 release: ElizaOS just released its latest version v0.25.8, this update reduces the number of plugins removed from the main repository Redundancy and simplify the installation process – a major improvement to the user experience. New features include support for more large language models (LLMs), such as NEAR AI and Secret Network models, and a dynamic plug-in system for enhanced flexibility.

Future expectations:

With the plug-in separation and multi-model support in v0.25.8 version With the successful implementation, future versions of ElizaOS may introduce stronger cross-chain compatibility, not limited to existing integrations, thereby supporting more complex financial, gaming and social use cases. Its open source nature and community-driven plug-in ecosystem are expected to drive this process, and developers may contribute more domain-specific toolkits, such as dedicated agents for 3D content generation or decentralized identity management for the metaverse.

In terms of functionality, ElizaOS may deepen its multimodal capabilities, integrate text, image and audio processing more seamlessly, and may even introduce native AI Driven real-time decision-making engine, suitable for scenarios such as supply chain management or dynamic NFT market.

Project introduction:

G.A.M.E is an AI proxy framework developed by VirtualsProtocol. Virtuals Protocol is a Base-based decentralizednetwork. It is committed to enabling autonomous AI agents to run on multiple platforms and integrate with blockchain technology to create a tokenized, proxy-driven economic system. G.A.M.E has attracted attention for its convenient SDK (Software Development Toolkit) and extended proxy capabilities, contributing to the Virtuals ecosystem, which has a total market capitalization of $6 billion and supports multiple high-value AI proxy projects.

Technical advantages:

Providing a low-code toolkit, suitable for non-technical users to quickly deploy agents. Compared with frameworks that require programming skills (such as ElizaOS or ARC), G.A.M.E significantly lowers the threshold for use.

Github stars:

131

https://github.com/Virtual-Protocol/virtuals-python

Latest developments:

Virtuals ecosystem repurchase and destruction plan: Virtuals Protocol announced the repurchase and destruction plan in mid-January, which had a significant impact on the G.A.M.E framework. Virtuals repurchased and destroyed 25 AI proxy tokens, including 1.6 million GAME tokens, using 13 million VIRTUAL tokens ($11.7 million).

GOAT SDK integration: In mid-to-late January, G.A.M.E announced integration with the GOAT SDK, which is a G.A.M.E agent to understand locks with "more than 200 on-chain actions". This collaboration is described as a “game-changing” that enhances the blockchain interactivity of the agent.

DeepSeek Integration: In mid-February, G.A.M.E announced the integration of the high-performance large language model DeepSeek into the G.A.M.E framework. The addition of DeepSeek has enhanced the reasoning and dialogue capabilities of G.A.M.E agents, which may improve the agent's ability to handle complex cross-platform tasks and become a key differentiation advantage of G.A.M.E.

Multi-platform autonomous upgrade: In mid-to-late February, G.A.M.E released a major upgrade of the SDK, giving AI agents the ability to run autonomously on X, Discord, Telegram and Farcaster, so that it is not just plug-ins, but real Multi-platform autonomy. This update jumps from a static plug-in to dynamic cross-platform proxy coordination—for example, a proxy can start tasks on Telegram and complete on Discord.

Future expectations:

Based on its SDK that has achieved amazing growth in the past three months, future versions may further optimize the development experience and launch more powerful toolsets such as built-in smart contract templates or real-time data analysis modules. On a technical level, G.A.M.E may deepen its multi-platform autonomy capabilities, extending beyond current X, Discord, Telegram and Farcaster integrations to a wider range of decentralized social networks. In addition, continuous integration of high-performance language models such as DeepSeek may drive G.A.M.E agents in Breakthroughs in natural language processing and decision reasoning make them suitable for a wider range of scenarios such as automated customer support or on-chain governance.

Project introduction:

RIG is an open source AI proxy framework developed by ARC, written in Rust. It aims to simplify the creation of autonomous AI proxy by providing a modular architecture, supports multiple large language models (LLMs) for memory management. Vector database and scalable tool integration.

Technical advantages:

Based on Rust's memory security and zero-cost abstraction, RIG performs well in resource-intensive tasks and is more suitable for enterprise-level applications.

Github stars:

3.1K

https://github.com/0xPlaygrounds/rig

Latest developments:

GitHub repository launch and documentation: RIG's official GitHub repository was released late last December and was released with basic documentation outlining installation instructions, supported models, and a simple "Hello World" proxy example. p>

Support mainstream models and tools: In January this year, RIG consolidated support for mainstream LLM, including standard utilities (such as web crawling, file I/O ) etc.

Agent Launchpad FORGE: In mid-February, ARC launched "ARC FORGE, a Launchpad for proxy-driven tokens, also announced its first project AskJimmy, an AI-driven trading platform. FORGE uses the RIG framework to enable AI agents to manage token issuance and integrate with blockchain for decentralization. Trading.

Future expectations:

RIG's Rust feature, while limiting entry for beginners, will attract professional developers, especially in scenarios where low latency and high throughput, such as GameFi or DeFi protocols. In the future, ARC It is possible to reduce the learning curve through richer documentation, tutorials and pre-built templates, and accelerate the development of the community plug-in ecosystem, such as dedicated adapters for Solana or Base blockchains.

Project introduction:

ZerePy is a Python framework developed based on Zerebro's back-end technology. It was launched by the Zerebro team in collaboration with ai16z. It is called "the first Python-based AI proxy framework in the Crypto field." ZerePy extracts Zerebro's core functions ( Such as content generation and social platform interaction) and encapsulate it as a tool set that developers can use directly.

Technical advantages:

ZerePy framework is good at art generation (such as NFT, music). Compared with more functional frameworks, it is unique in the fields of entertainment and social media, and the Python-based architecture is very friendly to AI/ML developers. p>

Github stars:

553

https:/ /github.com/blorm-network/ZerePy

Latest developments:

With Zerebro Ecology Integration of the system and Zentients Launchpad: In early January this year, ZerePy connected with Zerebro's tokenized ecosystem, expanding its practicality as an independent framework.

Increased community interest: Early adoption focused on lightweight applications (such as X automation, content creation), ZerePy's Python foundation attracted a wider audience than Rust or TypeScript frameworks.

TEE in ZerePy: In mid-to-late January, the upgraded ZerePy can run in a trusted execution environment (TEE) for secure cloud deployment.

Future expectations:

ZerePy's Python foundation provides it with extensive community support and ecological compatibility, and is expected to become the preferred tool for Python developers to build Web3-driven AI agents, especially in the fields of social media automation and decentralized creative applications. Within the Zerebro ecosystem, the development of ZerePy may be deeply bound to Zentients Launchpad, supporting the incubation and deployment of several new agent projects.

REI is an AI proxy framework designed to bridge the gap between AI and blockchain and solve technical incompatibility problems such as computing resource conflicts and data structure mismatch. REI adopts a modular architecture and utilizes an "oracist bridge" ” (Oracle Bridge) connects on-chain and off-chain data, enabling AI agents to conduct real-time analysis and decision-making in a decentralized environment.

Technical advantages:

Focusing on complex distributed architecture design, it is more suitable for developers who need high-end customization than simple and easy-to-use frameworks (such as G.A.M.E).

Github stars:

No public link yet

Latest developments:

Integration with Base Blockchain: In early January, REI was integrated with Base to improve scalability and Reduce Gas costs. Base's low-cost, high-throughput environment complements REI resource-intensive AI operations. The oracle bridge connects Base's on-chain data to off-chain AI inference, allowing the agent to adjust DeFi parameters (such as liquidity pool ratio) in real time.

Dynamic NFT use case demonstration: In mid-to-late January, a demonstration on X demonstrated that REI agents can update dynamically based on on-chain activities (such as user's transaction history) NFT attributes highlight the practicality of REI.

Future expectations:

Based on its current oracle bridge and modular proxy system, Future releases may further optimize on-chain-off-chain collaboration efficiency, such as enhancing privacy protection and computing speed by integrating more efficient zero-knowledge proofs (ZKP) or trusted execution environment (TEE). This will enable REI agents to handle more complex workloads such as dynamic risk management of large-scale DeFi protocols or real-time supply chain optimization. With the successful integration with the Base chain, REI may further cooperate with the Layer2 ecosystem (such as Arbitrum or Optimism) to use low-cost and high-throughput environments to promote the implementation of enterprise-level applications.

Project introduction:

Swarms is an open source framework used to coordinate multiple AI agent emphasizes modularity, scalability and lightweight design. Unlike a single proxy system, Swarms implements distributed task execution, specialized proxy collaboration solves problems—for example, one proxy analyzes data, another executes transactions, and a third manages output.

Technical advantages:

Focusing on proxy cluster collaboration, simulating natural collective intelligence (such as bee colonies), it is more efficient when dealing with complex tasks than a single agent-based framework (such as ZEREBRO or G.A.M.E).

Github stars:

18.9K

https://github.com/openai/swarm

Latest developments:

Market launch on the Swarms platform: Last December, Swarms launched a market that allows developers to discover and monetize agents, tools and prompt words. This marketplace integrates with the Swarms SDK, where developers can deploy agents (for example for transactions or content generation) and earn SWARMS. It supports inter-agent interactions, forming groups that adapt and improve over time, similar to natural ecosystems.

Company Adoption Milestone: CryptoSlate reported in January this year that Swarms has deployed more than 45 million agents in the financial, insurance and medical fields to serve top companies.

Swarms7.2.6 version released: In mid-to-late February, Swarms7.2.6 version was released, emphasizing that multiple bugs were fixed and new features were added. This update enhances proxy collaboration through roles and improved group architectures such as RoundRobin, GroupChat, ConcurrentWorkflow, and AgentRearrange.

Proxy and multi-proxy API: Swarms has recently launched the proxy and multi-proxy APIs, aiming to simplify the integration of group architectures (such as Concurrent, Sequential, HierarchicalSwarm, RoundRobin ). These managed APIs will support multiple models to improve application development capabilities.

Future expectations:

Swarms' open source properties and the upcoming proxy and multi-proxy API It indicates that its developer ecosystem will expand rapidly. In the future, its SDK may fully support cross-platform deployment, using its lightweight design and fault tolerance mechanism (automatically adapted after proxy failure) to achieve none.Multi-chain operation. In addition, with the improvement of the memory system, Swarms agents may have long-term context memory and support task planning across time dimensions. In terms of community and market impact, its openness and Solana's low-cost advantages will attract more developers, especially in the DeFi and GameFi fields.

With low-code development, high-performance architecture, multimodal capabilities, and seamless integration with blockchain, these AI proxy frameworks have successfully responded to the market's needs. The need for efficiency, creativity and practicality. Looking ahead, these frameworks are expected to break through with the popularization of high-performance language models, the maturity of high-throughput blockchains, and the further expansion of the tokenized economy. The existing boundaries have developed stronger cross-chain compatibility, privacy protection mechanisms and long-term task planning capabilities, and promoted the deep integration of Web3 in social, gaming, finance and even real-world applications.

Compared with the development path of traditional AI agents, these proxy frameworks rooted in the Web3 direction still have a long way to go. After experiencing the hype period, these agent development teams need to focus more on development and commercial expansion in order to usher in the next explosion.