Author: arndxt
Compiled by: Deep Tide TechFlow
Introduction
Crypto x AI has become a hot topic, and Virtuals have surged again (as of the time of compiling this article, the market value of Virtuals has exceeded $2.4 billion, with a 24-hour increase of 24%). Besides Virtuals, which other Crypto x AI frameworks are worth paying attention to? What are the similarities and differences between different frameworks?
Deep Tide has compiled this article, providing an in-depth analysis of the technical architecture, market positioning, and potential impact of the four major frameworks: Eliza ($AI16Z), GAME ($VIRTUAL), Rig ($ARC), and ZerePy ($ZEREBRO).
Main Text
In the Crypto x AI field, there are currently four major frameworks:
Eliza ($AI16Z)
GAME ($VIRTUAL)
Rig ($ARC)
ZerePy ($ZEREBRO)
These frameworks are clearly positioned to meet the diverse needs of developers.
Eliza holds about 60% of the market share thanks to its first-mover advantage and active TypeScript community; GAME (~20%) focuses on gaming and metaverse applications and is rapidly gaining popularity.
Rig (~15%) is built on Rust, providing a high-performance modular design, making it very suitable for the Solana ecosystem; while ZerePy (~5%) is an emerging framework based on Python, focusing on creative output and social media automation. Currently, the total valuation of these frameworks is $1.7 billion, and as AI-driven crypto applications continue to expand, the market size could exceed $20 billion, making a market-cap-weighted investment strategy a worthwhile consideration. Each framework occupies a unique market segment—Eliza focuses on social and multi-agent, GAME targets gaming and the metaverse, Rig is dedicated to enterprise-level performance, while ZerePy is aimed at creative community applications. These frameworks are more complementary to each other than directly competitive.
1. Overview and Market Position
(Original English table from @arndxt_xo, compiled by Deep Tide TechFlow)
1.1 Eliza ($AI16Z)
Market Share: ~60%
Market Value: $90 million
Core Language: TypeScript
Main Advantages: First-mover advantage, large GitHub community (6,000+ stars, 1,800 forks)
Key Applications: Supporting multi-agent simulations, cross-platform social interactions
As one of the earliest AI agent frameworks in the field, Eliza holds a dominant position. Its first-mover advantage is due to a large developer community, which not only accelerates the iteration of framework functions but also promotes widespread adoption by users. The TypeScript-based tech stack makes it an ideal choice for developers engaged in web development, thus attracting a broad developer base.
1.2 GAME ($VIRTUAL)
Market Share: ~20%
Market Value: $30 million
Core Language: API/SDK-based language-agnostic design
Main Advantages: Rapid adoption in the gaming industry, supporting real-time agent interaction
Key Applications: Procedural content generation, adaptive NPC behavior
GAME is designed for gaming and metaverse applications. Its API-based architecture allows developers to easily integrate into existing projects, while its close connection to the $VIRTUAL ecosystem promotes rapid ecological development. So far, over 200 projects have adopted this framework, with an average daily request volume of up to 150,000, and it continues to grow weekly. GAME's no-code integration feature is particularly valued, allowing teams that wish to deploy projects quickly to achieve functionality online without delving deeply into technical details.
1.3 Rig ($ARC)
Market Share: ~15%
Market Value: $16 million
Core Language: Rust
Main Advantages: High-performance modular design optimized for the Solana ecosystem
Key Applications: Enterprise-level performance needs, complex transaction processing
Rig is a performance-focused framework built in Rust, taking full advantage of Solana's high throughput. Its modular design allows developers to flexibly customize functionalities according to specific needs, making it particularly well-suited for enterprise-level applications requiring high performance and low latency. Although its market share is relatively small, its positioning within the Solana ecosystem makes it particularly attractive for developers involved in high-frequency trading and complex smart contract execution.
1.4 ZerePy ($ZEREBRO)
Market Share: ~5%
Market Value: $30 million
Core Language: Python
Main Advantages: Focus on creative output and social media automation
Key Applications: Generative content, community interaction tools
As an emerging framework in the field, ZerePy, with Python as its core language, lowers the development threshold, attracting many creative developers and content creators. Its focus on generative content and social media automation makes it an ideal choice for creative communities and marketing teams. Although its market share is currently small, its growth potential should not be overlooked.
2. Technical Architecture and Core Components
Eliza ($AI16Z)
Multi-Agent Systems: Support multiple AI agents to cooperate or compete in the same operating environment, suitable for complex interactive scenarios.
Memory Management (RAG): Enhances the contextual memory ability of generated content by retrieving relevant information, supporting long-term interactions.
Plugin System: Allows the community to develop extended functions, such as voice, text parsing, and processing multimedia files (like PDF, images).
Extensive Model Support: Compatible with local open-source large language models (LLM) or cloud-based APIs (like OpenAI, Anthropic).
Eliza's architecture is designed around multimodal communication, making it very suitable for social, marketing, and community-oriented AI applications. It supports easy integration into platforms like Discord, X (formerly Twitter), and Telegram, providing developers with rich extension options. However, during large-scale deployments, effective management of multiple agents' personalities and memory modules is needed to ensure system stability and efficiency.
GAME ($VIRTUAL)
API + SDK Model: Provides a straightforward agent integration solution for game studios and metaverse projects.
Agent Prompt Interface: Coordinates the interaction between user input and the agent's strategy engine, optimizing the player experience.
Strategy Planning Engine: Divides agent logic into high-level goal planning and low-level strategy execution, enhancing the flexibility of character behavior.
Blockchain Integration: Supports on-chain wallet operations and decentralized agent governance, enhancing asset management capabilities in the metaverse.
GAME's architecture is optimized for gaming and metaverse scenarios, prioritizing real-time performance needs while supporting the dynamic adaptability of agents. Its strategy planning engine helps game characters set goals and adjust actions in real time, providing players with a more immersive experience. Although its architecture can be extended to other areas, its design is still primarily focused on virtual worlds and procedurally generated applications.
Rig ($ARC)
Rust Workspace Structure: To achieve clear and modular design, functions are divided into multiple independent packages.
Provider Abstraction Layer: Unifies the interaction methods with various LLM providers (like OpenAI and Anthropic).
Vector Storage Integration: Supports various backends (MongoDB, Neo4j) to realize contextual retrieval functions.
Agent System: Integrates retrieval-augmented generation (RAG) and the use of dedicated tools.
Rig's high-performance architecture benefits from Rust's concurrency model, making it very suitable for enterprise application scenarios requiring strict resource management. By employing a layered abstraction design philosophy, Rig provides very high reliability, but Rust's steep learning curve may limit developer participation.
ZerePy ($ZEREBRO)
Python-based: Designed for AI/ML developers familiar with Python libraries and development processes, easy to get started.
Modular Zerebro Backend: Provides creative content generation capabilities, especially suitable for social media and arts.
Agent Autonomy: Focuses on 'creative output', including memes (internet popular culture content), music, and NFT generation tasks.
Social Platform Integration: Built-in modules similar to Twitter, such as posting, replying, and retweeting operations.
ZerePy offers solutions for Python developers who wish to rapidly deploy agents on social platforms. Although its application scope is narrower than Eliza or Rig, ZerePy excels in artistic creation or entertainment-driven scenarios, especially holding unique advantages in decentralized communities.
3. Comparison Dimensions
3.1 Ease of Use
Eliza: Pursues balance in design; although the complexity of multi-agent systems brings a certain learning curve, the strong TypeScript developer community provides good support.
GAME: Designed for non-technical users, especially in the gaming field, offering no-code or low-code development solutions that lower the barrier to entry.
Rig: Requires a higher level of expertise from developers, as the strictness of Rust necessitates certain professional skills, but its high performance and reliability provide rich rewards for the efforts of developers.
ZerePy: Very friendly to Python users, especially suitable for developers engaged in creative or media-related AI tasks.
3.2 Scalability
Eliza: The V2 version introduces a scalable message bus and optimized concurrency capabilities, but task scheduling and resource allocation for multi-agent systems still require careful management.
GAME: Scalability depends on real-time game demands and the stability of the blockchain network; as long as the limitations of game engines can be effectively controlled, performance remains excellent.
Rig: Naturally possesses high scalability due to Rust's asynchronous runtime, making it very suitable for high-throughput and enterprise-level workloads.
ZerePy: Scalability mainly relies on community-driven efforts, suitable for creative and social media fields, but support for large enterprise-level loads is relatively limited.
3.3 Adaptability
Eliza: The most adaptive, featuring a plugin system, extensive model support, and cross-platform integration capabilities, suitable for various application scenarios.
GAME: Highly adaptable in the gaming field, seamlessly integrates with various game engines, but its applicability is relatively weak in other areas.
Rig: Suitable for data-intensive or enterprise tasks, supports flexible selection of various large language models and vector storage to meet complex scenario needs.
ZerePy: Focused on creative output, easily extensible relying on the Python ecosystem but has a narrower application domain.
3.4 Performance
Eliza: Optimized for social media and conversational tasks, its performance relies on the quality and response speed of external model APIs.
GAME: Provides excellent real-time performance in dynamic in-game contexts, with specific performance depending on the coordination between agent logic and blockchain overhead.
Rig: With the concurrency capabilities and memory safety of Rust, its performance is outstanding, especially suitable for complex large-scale AI processing tasks.
ZerePy: Performance mainly depends on the execution speed of Python and model invocation efficiency, sufficient to support social and content creation tasks, but not suitable for enterprise-level high throughput demands.
4. Advantages and Limitations
(Original English table from @arndxt_xo, compiled by Deep Tide TechFlow)
5. Market Potential and Prospects
The total market value of the four frameworks is currently $1.7 billion. If AI and the cryptocurrency (Crypto) field can achieve explosive growth like L1 blockchains, its market potential could exceed $20 billion. For investors, a market-cap-weighted strategy may be a wiser choice, especially as these frameworks serve different market domains and may benefit from the overall market uptrend.
Eliza ($AI16Z): With a mature ecosystem, a strong codebase, and upcoming V2 features (like Coinbase agent toolkit and trusted execution environment (TEE) support), it is expected to maintain its leading market share.
GAME ($VIRTUAL): The pace of adoption in the gaming and metaverse fields is accelerating, with the synergistic effects of the $VIRTUAL ecosystem ensuring continuous developer attention.
Rig ($ARC): May become the 'hidden gem' of enterprise AI on Solana. With the progress of the handshake plan, it is expected to replicate the successful model of other chain-specific frameworks.
ZerePy ($ZEREBRO): Although positioned relatively niche, it focuses on creativity and arts, supported by the Python ecosystem and a strong community momentum. These areas are often overlooked by more general solutions.
6. Comprehensive Comparative Insights
6.1 Tech Stack and Learning Curve
Eliza (TypeScript): Achieves a good balance between ease of use and feature richness.
GAME: Provides a simple and easy-to-use API for game development, but its application scope is relatively limited.
Rig (Rust): Pursues extreme optimization of performance at the cost of higher complexity.
ZerePy (Python): Simple to operate in creative applications but lacks widespread enterprise-level applicability.
6.2 Community and Ecosystem
Eliza: Has the largest community influence on GitHub, reflecting its wide applicability and strong community support.
GAME: Rapidly growing in the gaming and metaverse fields, benefiting from the support of the $VIRTUAL ecosystem.
Rig: Although the developer community is small, it has strong technical capabilities and focuses on high-performance application scenarios.
ZerePy: A niche community built around creativity and decentralized art, further enhancing its ecological influence through collaboration with Eliza.
6.3 Future Growth Catalysts
Eliza: The upcoming plugin registry and TEE integration may further consolidate its market leadership.
GAME: Attracting more non-technical users through the expansion of the $VIRTUAL ecosystem, driving growth.
Rig: Potential partnerships with Solana and enterprise-level positioning may bring significant growth after expanding the developer community.
ZerePy: Relying on Python's popularity in AI development, as well as the trend of creative and community-driven projects, further consolidating its position in niche markets.
