Llama Stack vs Mastra: Agent Frameworks Comparison
Compare Llama Stack and Mastra side by side. Both are tools in the Agent Frameworks category.
Quick Comparison
| Category | Agent Frameworks | Agent Frameworks |
| Pricing | — | Open Source |
| Best For | — | TypeScript developers who want a modern framework for building production AI agents |
| Website | github.com | mastra.ai |
| Key Features | — |
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| Use Cases | — |
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When to Choose Llama Stack vs Mastra
- TypeScript-native agent development
- Building AI workflows with tool use
- Agent state management
How to Choose a Agent Frameworks Tool
Key criteria to evaluate when comparing Agent Frameworks solutions:
About Llama Stack
Llama Stack is Meta's standardized API and SDK for building AI applications on top of Llama models. It provides a unified interface for inference, safety, memory, and agentic workflows — with swappable providers for local, cloud, and on-device deployment. As the official framework for the Llama ecosystem, it is becoming the default for teams building on open-source Llama models.
About Mastra
Mastra is a TypeScript-first agent framework for building production AI applications. It provides primitives for agents, workflows, RAG, integrations, and memory with a focus on developer experience and type safety. Mastra is designed for full-stack TypeScript developers who want to build AI features without leaving their existing tech stack.
What is Agent Frameworks?
Developer frameworks and SDKs for building autonomous AI agents with tool use, planning, multi-step reasoning, and orchestration capabilities.
Browse all Agent Frameworks tools →