FastAgency vs LlamaDeploy

Side-by-side comparison of two AI agent tools

Short answer

  • FastAgency has had no commit in 9 months; LlamaDeploy is actively maintained (36 commits in the last 90 days).
  • FastAgency is growing faster: +3 GitHub stars in the last 30 days vs +-257 for LlamaDeploy.
  • Pick FastAgency for: the fastest way to bring multi-agent workflows to production. Pick LlamaDeploy for: deploy your agentic worfklows to production.

From GitHub data refreshed daily.

FastAgencyopen-source

The fastest way to bring multi-agent workflows to production.

LlamaDeployopen-source

Deploy your agentic worfklows to production

Metrics

FastAgencyLlamaDeploy
Stars548454
Star velocity /mo2.5396825396825395-257.3015873015873
Commits (90d)036
Releases (6m)010
Overall score0.180390999481865850.4525423118123008

Pros

  • +Unified interface for deploying AG2 workflows to production with minimal code changes
  • +Supports both web chat applications and REST API services from the same codebase
  • +Built-in scaling capabilities with distributed architecture and message broker coordination
  • +无缝部署体验：将notebook代码转换为生产服务只需最少的代码修改，显著降低了从原型到生产的迁移成本
  • +灵活的架构设计：hub-and-spoke模式支持组件级别的替换和扩展，可以独立升级消息队列等基础设施而不影响业务逻辑
  • +生产级可靠性：内置重试机制、失败处理和容错能力，确保代理工作流在生产环境中的稳定运行

Cons

  • -Dependent on AG2 framework, limiting flexibility to other agent frameworks
  • -Relatively small community with 532 GitHub stars compared to major frameworks
  • -Limited documentation available in the provided materials for advanced features
  • -学习曲线：需要熟悉LlamaIndex生态系统和工作流概念，对新手可能存在一定的入门门槛
  • -生态依赖：主要绑定LlamaIndex框架，如果需要集成其他AI框架可能需要额外的适配工作
  • -资源开销：作为多服务架构框架，在小型项目中可能存在过度工程的问题

Use Cases

  • •Deploying AG2 multi-agent chatbots as web applications for customer service or support
  • •Creating REST API services that expose agent workflows for integration with existing systems
  • •Building scalable distributed agent systems that coordinate across multiple servers or datacenters
  • •AI代理系统产品化：将研发阶段的智能代理工作流部署为生产级微服务，支持大规模用户访问
  • •企业级AI工作流编排：构建复杂的多步骤AI处理流程，如文档分析、数据处理和决策支持系统
  • •可扩展的AI API服务：将单一的AI工作流拆分为多个独立服务，实现水平扩展和高可用性部署
View FastAgency DetailsView LlamaDeploy Details

FAQ

Which is more popular, FastAgency or LlamaDeploy?
FastAgency has more GitHub stars (548 vs 454).
Which is more actively developed, FastAgency or LlamaDeploy?
LlamaDeploy had more commits in the last 90 days (36 vs 0).
Should I use FastAgency or LlamaDeploy?
Compare their capabilities, limitations and "best for" notes above. Both are open source, so trying each on a small task is the fastest way to decide.
FastAgency vs LlamaDeploy (2026): GitHub Stats, Features & Which to Choose