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LlamaIndex Agents vs Mastra
Side-by-side comparison of LlamaIndex Agents and Mastra — features, pricing, performance scores, and which to choose for your AI agents.
View All Framework ComparisonsQuick Verdict
| Dimension | LlamaIndex Agents | Mastra | Winner |
|---|---|---|---|
Ease of Use | 4/5 | 4/5 | Tie |
Scalability | 4/5 | 4/5 | Tie |
Documentation | 5/5 | 4/5 | LlamaIndex Agents |
Community | 5/5 | 3/5 | LlamaIndex Agents |
Performance | 4/5 | 4/5 | Tie |
Overall: LlamaIndex Agents wins 2 categories, Mastra wins 0, 3 tied
Feature Comparison
| Feature | LlamaIndex Agents | Mastra |
|---|---|---|
| Primary Language | Python | TypeScript |
| License | MIT | MIT |
| Pricing | Open Source + Cloud | Open Source |
| GitHub Stars | 44,600 | 7,500 |
| Difficulty | Intermediate | Intermediate |
| Enterprise Ready | ||
| Community Size | Very Large | Medium |
| Category | RAG & Knowledge | Multi-Agent Systems |
Pros & Cons
LlamaIndex Agents
Advantages
Best-in-class for RAG applications
Excellent data connectors and loaders
Strong documentation and examples
Active community and development
MIT license
LlamaCloud for managed services
Works well with LangChain
Limitations
Primarily focused on RAG not general agents
Agent features less mature than core RAG
Can be complex for simple use cases
LlamaCloud requires subscription
Mastra
Advantages
TypeScript-first framework
Good for JavaScript developers
YC-backed with funding
MIT license
Quick development focus
Limitations
Very new framework
Small community
Limited documentation
Fewer integrations than Python frameworks
Best Use Cases
LlamaIndex Agents
Document Q&A systems
Knowledge base retrieval
Semantic search applications
Chat over documents
Agent-based data retrieval
Research assistants
Mastra
TypeScript AI applications
Next.js AI integrations
Node.js agent systems
Rapid MVP development
Getting Started
LlamaIndex Agents
Installation
pip install llama-index
Mastra
Installation
npm install @mastra/core
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