llama-cpp-agent vs Mastra
Side-by-side comparison of two AI agent tools
Short answer
- llama-cpp-agent has had no commit in 6 months; Mastra is actively maintained (4,109 commits in the last 90 days).
- Mastra is growing faster: +968 GitHub stars in the last 30 days vs +6 for llama-cpp-agent.
- Pick llama-cpp-agent for: python framework for LLM chat, structured output, function calling, RAG, and agent chains. Pick Mastra for: from the team behind Gatsby, Mastra is a framework for building AI-powered applications and agents.
From GitHub data refreshed daily.
llama-cpp-agentfree
Python framework for LLM chat, structured output, function calling, RAG, and agent chains
Mastrafree
From the team behind Gatsby, Mastra is a framework for building AI-powered applications and agents with a modern TypeScript stack.
Metrics
| llama-cpp-agent | Mastra | |
|---|---|---|
| Stars | 659 | 28.5k |
| Star velocity /mo | 5.684210526315789 | 968.3684210526316 |
| Commits (90d) | 0 | 4.1k |
| Releases (6m) | 0 | 10 |
| Downloads (30d, npm + PyPI) | 603 | 3.1M |
| Overall score | 0.18581044753131928 | 0.8983723604743185 |
Pros
- +引导采样技术让未微调模型也能进行函数调用和结构化输出
- +支持多种后端提供商(llama-cpp-python、TGI、vllm等)提供良好兼容性
- +功能全面涵盖聊天、函数调用、RAG和代理链等核心能力
- +统一的多提供商接口支持 40+ AI 模型提供商，避免供应商锁定
- +完整的 AI 应用工具链包括代理、工作流、人机交互和上下文管理
- +TypeScript 原生支持和现代技术栈集成，开发体验优秀
Cons
- -项目已不再维护，官方建议迁移到其他框架
- -对于简单用例可能存在过度设计的复杂性
- -作为相对较新的框架，生态系统和社区资源可能有限
- -多功能集成可能带来学习曲线，需要时间掌握各个组件
- -文档和最佳实践可能还在完善中，缺少大规模生产案例
Use Cases
- •构建具有函数调用能力的对话代理系统
- •实现带文档检索的RAG应用程序
- •从LLM中提取结构化数据和执行复杂的代理链工作流
- •构建需要多个 AI 模型协作的复杂智能代理系统
- •开发需要人机交互审批流程的自动化工作流应用
- •快速原型验证 AI 产品概念并扩展到生产环境
FAQ
- Which is more popular, llama-cpp-agent or Mastra?
- Mastra has more GitHub stars (28,525 vs 659).
- Which is more actively developed, llama-cpp-agent or Mastra?
- Mastra had more commits in the last 90 days (4,109 vs 0).
- Should I use llama-cpp-agent or Mastra?
- Compare their capabilities, limitations and "best for" notes above. Trying each on a small task is the fastest way to decide.