Original author: amdxt

Compiled by: Luke, Mars Finance

There are four major frameworks in the field of Crypto x AI:

  • Eliza ($AI16Z)

  • GAME ($VIRTUAL)

  • Rig ($ARC)

  • ZerePy ($ZEREBRO)

They provide differentiated solutions for different developer needs.

Eliza dominates with about 60% of the market share thanks to its first-mover advantage and large TypeScript community; GAME (about 20%) focuses on games and metaverse applications and quickly gains market favor; Rig (about 15%) is based on Rust and emphasizes performance-oriented modular design, which fits the Solana ecosystem; and ZerePy (about 5%) is based on Python and is aimed at creative output and social media automation.

The total valuation of the four frameworks is $1.7 billion, and it is expected that the market size may exceed $20 billion with the expansion of AI-driven encryption applications. Investment strategies based on market capitalization weighting may be attractive because they each occupy a unique market segment and exist in a complementary rather than competitive relationship.

1. Framework Overview and Market Position

Eliza ($AI16Z)

Market share: about 60%

Market value: $900 million

Core language: TypeScript

Main advantages: first-mover advantage, large GitHub community (6000+ stars, 1.8K forks)

Focus: Multi-agent simulation, cross-platform social interaction

As one of the earliest AI agent frameworks in the field, Eliza has quickly gained market share with its first-mover advantage and active developer community. The TypeScript technology stack makes it a natural choice for Web developers and is widely popular.

GAME ($VIRTUAL)

Market share: about 20%

Market value: $300 million

Core language: Language-independent (API/SDK driven)

Key Advantages: Rapid adoption in the gaming industry, real-time agency capabilities

Focus: Procedural content generation, adaptive NPC behavior

GAME is designed specifically for games and the metaverse, and its API-driven architecture and deep binding to the $VIRTUAL ecosystem have led to significant growth (200+ projects, average daily requests of 150,000). The code-free integration approach also appeals to teams that prioritize rapid deployment.

Rig ($ARC)

Market share: about 15%

Market value: $160 million

Core language: Rust

Main advantages: high performance, modular design (enterprise level)

Focus: Pure applications based on Solana, enhanced search generation technology

Rig's Rust architecture is targeted at developers who value speed and resource management, and is suitable for data-intensive enterprise applications. Although the learning curve is steep, its modularity and reliability are very attractive.

ZerePy ($ZEREBRO)

Market share: about 5%

Market value: $30 million

Core language: Python

Key benefits: Community-driven creativity, social media automation

Focus: Agent deployment on social platforms, especially for artistic or niche content generation

ZerePy's Python foundation and focus on creative applications (such as NFTs, music, and digital art) have attracted a loyal user base. The partnership with Eliza has increased its exposure, but its narrow application scope has limited broader enterprise adoption.

2. Technical architecture and core components

Eliza ($AI16Z)

  • Multi-agent systems: Deploy multiple AI characters under a shared runtime.

  • Memory management (RAG): Towards long-term contextual support through retrieval-augmented generation.

  • Plugin system: supports community-developed extensions (such as voice, text, and media parsing).

  • Wide range of model support: Can integrate local open source LLM or cloud API (OpenAI, Anthropic).

Eliza's technical design focuses on multimodal communication, suitable for social, marketing or community AI agent application scenarios. Although it is easy to integrate (Discord, X, Telegram), large-scale use requires careful coordination.

GAME ($VIRTUAL)

  • API + SDK model: simplifies agent integration for games and Metaverse projects.

  • Agent prompt interface: coordinates the interaction between user input and the agent policy engine.

  • Strategy Planning Engine: Divides the logic into high-level goal planning and low-level execution strategy.

  • Blockchain Integration: Supports on-chain operations for decentralized proxy governance.

GAME's architecture is highly specialized for gaming or metaverse environments, prioritizing real-time performance and continuous agent adaptation. While it can be extended beyond gaming, the system is explicitly designed for virtual worlds and procedurally generated scenarios.

Rig ($ARC)

  • Rust workspace structure: Divide functionality into modular units.

  • Vendor Abstraction Layer: Unifies interactions with multiple LLM providers.

  • Vector storage integration: supports multiple backend retrieval such as MongoDB and Neo4j.

  • Proxy systems: embedding enhanced retrieval generation and professional tool use.

Rig's high-performance design benefits from Rust's concurrency model, making it ideal for enterprise environments that require strict resource management. It achieves conceptual clarity through layered abstractions and provides strong reliability, but Rust's learning curve may limit the number of developers.

ZerePy ($ZEREBRO)

  • Python framework: Easy to use for AI/ML developers who are familiar with Python workflows.

  • Modular Zerebro backend: Focused on social media and artistic creative content generation.

  • Agency autonomy: Focus on creative outputs like memes, music, and NFTs.

  • Social platform integration: built-in Twitter-like function commands (post, reply, retweet).

ZerePy fills the need for Python developers looking to deploy agents directly on social platforms. While its application scope is narrower than Eliza or Rig, ZerePy excels in art- or entertainment-driven use cases, especially in decentralized communities.

3. Comparison Dimensions

3.1 Usability

  • Eliza: Well-balanced, suitable for TypeScript developers, but with high complexity of multiple agents.

  • GAME: Designed for non-technical users in the gaming field, providing low-code solutions.

  • Rig: Rust's rigor leads to high performance, but requires a professional level.

  • ZerePy: The most user-friendly for Python, especially suitable for creative or media AI tasks.

3.2 Scalability

  • Eliza: Scales with V2 message bus and concurrency improvements.

  • GAME: Hooked with the real-time needs of the blockchain network.

  • Rig: A Rust-based asynchronous runtime that naturally supports high throughput.

  • ZerePy: Community driven extension, more focused on creative fields.

3.3 Adaptability

  • Eliza: The plugin system, wide model support, and cross-platform integration make it the most adaptable.

  • GAME: Focuses on gaming scenarios, but has less flexibility in other areas.

  • Rig: Suitable for data-intensive tasks, and can flexibly adapt to multiple LLMs and vector storage.

  • ZerePy: Suitable for Python ecosystem, but its scope is relatively narrow.

4. Advantages and limitations

5. Market potential and outlook

The current total market value of the four major frameworks is US$1.7 billion. If the AI ​​x Crypto field can replicate the explosive growth model of L1 blockchain, the market size is expected to exceed US$20 billion.

For investors who believe these frameworks serving different market segments will rise together in a broader “rising tide” scenario, a market-cap-weighted investment strategy may be a wise choice.

  • Eliza ($AI16Z) is expected to continue to maintain its market share leadership, further solidifying its dominance with its mature ecosystem, strong codebase, and upcoming V2 feature upgrades such as Coinbase agent kit integration and TEE support.

  • GAME ($VIRTUAL) will further increase its adoption in the gaming and metaverse space. The synergy with the $VIRTUAL ecosystem ensures continued developer attention, and its low-code integration approach will also attract more non-technical teams.

  • Rig ($ARC) As a potential stock for enterprise AI on Solana, Rig is expected to replicate the success of other on-chain dedicated frameworks as its Handshake Program matures. Its appeal continues to grow for enterprise scenarios that require high performance and reliability.

  • ZerePy ($ZEREBRO) Although its application scope is narrower, ZerePy benefits from strong community momentum and the Python ecosystem, and occupies a unique niche in creative and artistic applications that are often overlooked by more general solutions.

6. Conclusion

1. Technology stack and learning curve

Eliza (TypeScript) strikes a balance between accessibility and feature richness.

GAME provides an accessible API for games, but it may be niche.

Rig (Rust) maximizes performance at the expense of a higher complexity threshold.

ZerePy (Python) is simple enough for creative applications but lacks broader enterprise functionality.

2. Community and Ecosystem

Eliza: Largest presence on GitHub, reflecting strong community engagement and broad applicability.

GAME: The rapid growth of the gaming and metaverse circles, thanks to the support of $VIRTUAL.

Rig: A smaller but skilled developer community focused on high-performance use cases.

ZerePy: A growing niche community built around creativity and decentralized art, enhanced by Eliza’s collaboration.

3. Future growth catalysts

Eliza: The new plugin registry and TEE integration may further consolidate its leadership.

GAME: Active expansion through $VIRTUAL’s ecosystem; accessible to non-technical users.

Rig: Potential Solana partnerships and enterprise focus could lead to strong growth once developer traction increases.

ZerePy: Leveraging Python's popularity in the AI ​​space and the cultural momentum around creative, community-driven projects.