Author: Arndxt, Threading on the Edge; Translator: Golden Finance Xiaozou
There are four main frameworks in the Crypto x AI field: Eliza (AI16Z), GAME (VIRTUAL), Rig (ARC), and ZerePy (ZEREBRO).
All four frameworks cater to different development needs.
Driven by first-mover advantage and a thriving TypeScript community, Eliza holds a dominant position with around 60% market share, while GAME (with around 20% market share) targets rapidly adopted gaming and virtual world applications.
Rig (with about 15% market share) is developed in Rust, providing performance-oriented modularity suitable for the Solana ecosystem, while the new Python-based architecture ZerePy (with about 5% market share) focuses on creative output and social media automation. The total market value of these frameworks is $1.7 billion, and as AI crypto applications expand, their total market value could exceed $20 billion, making a market cap-weighted approach potentially attractive. Each framework occupies its unique market—social and multi-intelligence agents (Eliza), gaming/virtual worlds (GAME), enterprise performance (Rig), and creative community usage (ZerePy)—offering complementary options rather than direct competition.
1. Overview of the four frameworks and their market positioning
(1) Eliza ($AI16Z)
● Market share: ~60%
● Market Value: $900 million
● Core language: TypeScript
● Main advantages: First-mover advantage, extensive GitHub community (over 6000 stars, 1800 forks)
● Focus: Multi-proxy simulation, cross-platform social engagement
As one of the earliest AI proxy frameworks in the field, Eliza dominates the market. Its first-mover advantage is supported by a large contributor community, accelerating development speed and promoting user adoption. Eliza's TypeScript stack makes it highly suitable for developers working in web-based ecosystems, ensuring broad appeal.
(2) GAME (VIRTUAL)
● Market share: ~20%
● Market Value: $300 million
● Core language: (API/SDK-based; adopts a language-agnostic approach)
● Main advantages: Rapid adoption in the gaming industry, real-time proxy capabilities.
● Focus: Programmatic content generation, adaptive NPC behavior.
GAME is tailored for gaming and virtual world applications. Its API-driven architecture and close ties with the VIRTUAL ecosystem generate immense momentum: it has garnered over 200 projects, with 150,000 requests daily, and rapid weekly growth. GAME's no-code integration further attracts teams prioritizing rapid deployment over deep technical customization.
(3) Rig (ARC)
● Market share: ~15%
● Market Value: $160 million
● Core language: Rust
● Main advantages: Performance, modular design (enterprise-grade)
● Focus: Solana-based 'pure-play gaming', emphasizing retrieval-augmented generation.
Rig, built on a Rust architecture, caters to developers who prioritize speed, memory safety, and efficient concurrency. It is designed for 'enterprise-grade' or data-driven applications, particularly suitable for those on Solana. Despite the steep learning curve, Rig offers modular performance and reliability that can attract system-oriented developers.
(4) ZerePy (ZEREBRO)
● Market share: ~5%
● Market Value: $300 million
● Core language: Python
● Main advantages: Community-driven creativity, social media automation.
● Focus: Proxy deployment on social platforms, especially targeting artistic or niche output.
ZerePy is a latecomer, originating from Zerebro's core backend. Its Python foundation, coupled with a focus on creative applications (NFTs, music, and digital art), has attracted a passionate following. Its collaboration with Eliza has enhanced ZerePy's visibility, but the narrower domains ZerePy targets may limit widespread enterprise adoption.
2. Technical architecture and core components
(1) Eliza (AI16Z)
● Multi-proxy system: Deploys multiple AI personalities under a shared runtime.
● Memory Management (RAG): Implements retrieval-augmented generation pipelines for long-term context.
● Plugin system: Supports community-developed extensions focused on voice, text, and media parsing (e.g., PDF, images, etc.).
● Extensive model support: Integrates local open-source LLM or cloud APIs (OpenAI, Anthropic).
Eliza's technical design centers around multimodal communication, making it highly suitable for social, marketing, or community-based AI proxies. While it excels in easy integration (Discord, X, Telegram), large-scale usage will require careful orchestration of different proxy personalities and memory modules.
(2) GAME (VIRTUAL)
● API + SDK model: Simplifies agent integration for gaming companies and virtual world projects.
● Proxy prompt interface: Coordinates interactions between user input and proxy strategy engines.
● Strategic planning engine: Breaks down proxy logic into high-level goal planning and low-level strategy execution.
● Blockchain integration: Potential on-chain wallet operators for decentralized proxy governance.
GAME's architecture is highly customized for gaming or virtual environments, prioritizing real-time performance and continuous proxy adaptation. While its role is not limited to gaming, the system's design is clearly oriented towards virtual worlds and procedurally generated scenarios.
(3) Rig (ARC)
● Rust Workspace Structure: Separates functionality into multiple crates to ensure clarity and modularity.
● Provider Abstraction Layer: Norms for interaction with various LLM providers (OpenAI, Anthropic).
● Vector Store Integration: Supports multiple backends (MongoDB, Neo4j) for contextual retrieval.
● Agent System: Embeds retrieval-augmented generation (RAG) and dedicated tool usage.
Rig's high-performance design benefits from Rust's concurrency model, making it an ideal choice for enterprise environments that require strict resource management. Its concept is clear—providing strong reliability through layered abstractions—but the learning curve of Rust may limit the number of developers.
(4) ZerePy (ZEREBRO)
● Python-based development: Accessible to AI/ML developers familiar with Python codebases and workflows.
● Modular Zerebro backend: Provides creative content generation, particularly targeting social media and arts.
● Proxy Autonomy: Focus on 'creative output', such as meme, music, and NFT generation tasks.
● Social platform integration: Includes built-in commands similar to Twitter (post, reply, retweet).
ZerePy fills the gap for Python developers looking to deploy proxies directly on social platforms. While ZerePy's scope is narrower than Eliza or Rig, its art or entertainment-driven use cases thrive, especially in decentralized communities.
3. Comparison dimensions of the four frameworks
(1) Usability
● Eliza: Takes a balanced approach, with a moderate learning curve due to the complexity of multi-proxy but has a strong TypeScript developer base.
● GAME: Designed for non-technical adopters in the gaming field, providing no-code or low-code approaches.
● Rig: More challenging; Rust language requires strict expertise but can yield high performance and reliability.
● ZerePy: Easiest for Python users, especially in creative or media-focused AI tasks.
(2) Scalability
● Eliza: V2 iteration introduced an extensible message bus, improving concurrency, but multi-proxy concurrency can be complex.
● GAME: Scalability is related to real-time gaming demands and blockchain networks; performance will remain constant if game engine constraints are controlled.
● Rig: Naturally scalable through Rust's asynchronous runtime, suitable for high throughput or enterprise-grade workloads.
● ZerePy: Expansion is community-driven, mainly tested in creative or social media environments, with less emphasis on large enterprise loads.
(3) Adaptability
● Eliza: Highest adaptability to the plugin system, with broad model support for cross-platform integration.
● GAME: Specifically adapted to gaming environments, can be integrated into various game engines, but less suitable for other fields outside gaming.
● Rig: Suitable for data-intensive tasks or enterprise tasks; provides flexible vendor layers for multiple LLMs and vector storage.
● ZerePy: Focused on creative output; easy to scale in the Python ecosystem but has a narrower domain scope.
(4) Performance
● Eliza: Optimized for fast-paced social media or conversational tasks, its performance relies on external model APIs.
● GAME: Real-time performance dynamics in gaming; its success depends on the interaction between proxy logic and blockchain overhead.
● Rig: High performance due to Rust's concurrency and memory safety, very suitable for complex large-scale AI processes.
● ZerePy: Performance depends on Python's speed and model calls; generally sufficient for social/content tasks but not geared for enterprise-level throughput.
4. Advantages and limitations
5. Market potential and prospects
All four frameworks share a combined market value of $1.7 billion, and if the AI x Crypto industry follows the explosive growth pattern once seen in L1 blockchains, it could grow to over $20 billion. For investors who believe these frameworks (each serving different market niches) will rise together under a broader 'upward' trend, a market cap-weighted approach might be the most prudent.
● Eliza (AI16Z): Due to its existing ecosystem, robust codebase, and upcoming enhanced V2 (e.g., Coinbase proxy suite integration, TEE support), it may continue to hold the highest market share.
● GAME (VIRTUAL): Expected to further gain popularity in gaming/virtual worlds. The synergy with the VIRTUAL ecosystem ensures continuous interest from developers.
● Rig (ARC): Could become a 'hidden gem' for enterprise AI on Solana; as its partnership plans mature, it can replicate the traction of other chain-specific frameworks.
● ZerePy (ZEREBRO): While its scope is small, it benefits from strong community development momentum and the Python ecosystem, particularly targeting creative and artistic use cases often overlooked by more general solutions.
6. Comparative summary
(1) Tech stack and learning curve
● Eliza (TypeScript) strikes a balance between accessibility and rich functionality.
● GAME provides an accessible API for gaming, though it may target niche audiences.
● Rig (Rust) maximizes performance at the cost of a higher complexity threshold.
● ZerePy (Python) is straightforward for creative applications but lacks broader enterprise adoption.
(2) Community and ecosystem
● Eliza: Performs best on GitHub, reflecting strong community engagement and broad applicability.
● GAME: Benefiting from VIRTUAL's support, experiencing rapid growth in gaming and virtual world domains.
● Rig: Aimed at a technically proficient small-scale developer community, focusing on high-performance use cases.
● ZerePy: A growing niche community built around creativity and decentralized art, benefiting from partnerships with Eliza.
(3) Future growth catalysts
● Eliza: New plugin registry and TEE integration may further solidify its leadership.
● GAME: Actively expanding through the VIRTUAL ecosystem; accessible to non-technical users.
● Rig: May establish partnerships with Solana once developer traction increases, with a focus on enterprises potentially driving strong growth.
● ZerePy: Leverages Python's popularity in AI and the cultural momentum surrounding creative, community-driven projects.
