Which is more popular, hermes-agent or LlamaDeploy?

hermes-agent has more GitHub stars (250,690 vs 454).

Which is more actively developed, hermes-agent or LlamaDeploy?

hermes-agent had more commits in the last 90 days (32,889 vs 36).

Should I use hermes-agent 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.

hermes-agent vs LlamaDeploy

Side-by-side comparison of two AI agent tools

Short answer

hermes-agent is growing faster: +5,760 GitHub stars in the last 30 days vs +-257 for LlamaDeploy.
Pick hermes-agent for: the agent that grows with you. Pick LlamaDeploy for: deploy your agentic worfklows to production.

From GitHub data refreshed daily.

hermes-agentopen-source

The agent that grows with you

LlamaDeployopen-source

Deploy your agentic worfklows to production

Metrics

	hermes-agent	LlamaDeploy
Stars	250.7k	454
Star velocity /mo	5.8k	-257.3015873015873
Commits (90d)	32.9k	36
Releases (6m)	10	10
Overall score	0.9501761663348766	0.4525423118123008

Pros

+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

-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

•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 hermes-agent Details View LlamaDeploy Details

FAQ

Which is more popular, hermes-agent or LlamaDeploy?: hermes-agent has more GitHub stars (250,690 vs 454).
Which is more actively developed, hermes-agent or LlamaDeploy?: hermes-agent had more commits in the last 90 days (32,889 vs 36).
Should I use hermes-agent 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.