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LlamaIndex logoLlamaIndex
vs
Mastra logoMastra

LlamaIndex vs Mastra: Which is Better in 2026?

A comprehensive comparison of LlamaIndex and Mastra covering features, pricing, use cases, and which tool is the right choice for your needs.

⚡ Quick Verdict

Choose LlamaIndex if:

  • You want more affordable paid plans (from $97/mo)
  • You need a broader feature set (8 features vs 6)
  • You need document loaders for 100+ formats (pdf, word, notion, confluence) or advanced chunking and indexing strategies
  • Your primary focus is coding & development

Choose Mastra if:

  • You need agents, tools, and workflows as typescript primitives or built-in observability: traces, metrics, and logs
  • Your primary focus is ai agent infrastructure

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LlamaIndex vs Mastra: At a Glance

Attribute
LlamaIndex
Mastra
Pricing Model
Open Source
Freemium
Starting Price
Free to use
Starting at The framework is open source and free. Hosted platform tiers exist on the pricing page but the tier table is rendered client-side and not readable from a plain fetch, so no figure is quoted here.
Free Tier
✓ Yes
✓ Yes
Category
Coding & Development
AI Agent Infrastructure
Features Count
8 features
6 features
Shared Features
0 features in common

Pricing Comparison: LlamaIndex vs Mastra

Understanding the pricing differences between LlamaIndex and Mastra is crucial for making the right choice. Here's how their plans compare side by side.

LlamaIndex Pricing

Free$0forever
LlamaCloud from$97/month
View full LlamaIndex pricing →

Mastra Pricing

PlanThe framework is open source and free. Hosted platform tiers exist on the pricing page but the tier table is rendered client-side and not readable from a plain fetch, so no figure is quoted here.
View full Mastra pricing →

💡 Pricing takeaway: Both LlamaIndex and Mastra offer free tiers, making it easy to try before you buy. Compare the specific plans to find the best value for your use case.

Feature-by-Feature Comparison

Here's how every feature from LlamaIndex and Mastra stacks up.

Feature
LlamaIndex
Mastra
Document loaders for 100+ formats (PDF, Word, Notion, Confluence)
Advanced chunking and indexing strategies
Vector store integrations (Pinecone, Weaviate, Qdrant, etc.)
Query engines with sub-question decomposition
Knowledge graph indexing (KnowledgeGraph Index)
Multi-document agents
LlamaCloud: managed parsing and indexing
Evaluation toolkit for RAG pipelines
Agents, tools, and workflows as TypeScript primitives
Built-in observability: traces, metrics, and logs
Evals, experiments, scorers, and datasets
Studio for collaborative iteration on agents
Server product for cloud deployment
Extensive learning material — course, books, templates, workshops

What Makes Each Tool Unique

🔵 Unique to LlamaIndex

Features available in LlamaIndex but not in Mastra:

  • Document loaders for 100+ formats (PDF, Word, Notion, Confluence)
  • Advanced chunking and indexing strategies
  • Vector store integrations (Pinecone, Weaviate, Qdrant, etc.)
  • Query engines with sub-question decomposition
  • Knowledge graph indexing (KnowledgeGraph Index)
  • Multi-document agents
  • LlamaCloud: managed parsing and indexing
  • Evaluation toolkit for RAG pipelines

🟣 Unique to Mastra

Features available in Mastra but not in LlamaIndex:

  • Agents, tools, and workflows as TypeScript primitives
  • Built-in observability: traces, metrics, and logs
  • Evals, experiments, scorers, and datasets
  • Studio for collaborative iteration on agents
  • Server product for cloud deployment
  • Extensive learning material — course, books, templates, workshops

Use Case Recommendations

Best for: LlamaIndex

LlamaIndex (formerly GPT Index) is the leading data framework for LLM applications, specializing in connecting large language models to any data source. Where LangChain covers general agent orchestration, LlamaIndex excels at data ingestion, indexing, and retrieval — making it the go-to for enterprise RAG, document Q&A, and knowledge graph applications. LlamaCloud provides managed indexing infrastructure for production deployments.

Ideal use cases:

  • Teams or individuals who need document loaders for 100+ formats (pdf, word, notion, confluence)
  • Teams or individuals who need advanced chunking and indexing strategies
  • Teams or individuals who need vector store integrations (pinecone, weaviate, qdrant, etc.)
  • Teams or individuals who need query engines with sub-question decomposition
  • Anyone focused on llamaindex workflows
  • Anyone focused on rag workflows
Try LlamaIndex

Best for: Mastra

Mastra is a TypeScript framework for building AI agents and the applications around them, built by the team that previously created Gatsby. The core framework covers agents, tools, and workflows as first-class primitives, so a long-running agent is expressed in ordinary TypeScript rather than assembled from prompt strings and glue code. Around that framework sits a platform: observability with metrics, logs, and traces so agent runs are inspectable after the fact; evals, experiments, scorers, and datasets for measuring whether a change actually improved behavior; a Studio for collaborating on and iterating over agents; an Agent Builder; and a Server product that handles cloud deployment for agents. The company emphasizes agents that run for days rather than single-turn calls, which is what pushes the observability and scoring surface to the center of the product instead of leaving it as an add-on. Mastra is open source with roughly 26.7k GitHub stars and maintains a substantial learning surface — a quickstart, project templates, a video course, two books (Principles of Building AI Agents and Patterns of Building AI Agents), live workshops, and a weekly podcast — which makes it one of the more approachable entry points for JavaScript developers moving into agent work.

Ideal use cases:

  • Teams or individuals who need agents, tools, and workflows as typescript primitives
  • Teams or individuals who need built-in observability: traces, metrics, and logs
  • Teams or individuals who need evals, experiments, scorers, and datasets
  • Teams or individuals who need studio for collaborative iteration on agents
  • Anyone focused on typescript workflows
  • Anyone focused on agent framework workflows
Try Mastra

💻 Other Coding & Development Tools to Consider

LlamaIndex and Mastra aren't the only options. Here are other popular tools in the same space:

🏷️

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This page ranks for "LlamaIndex vs Mastra" — buyers comparing the two land here, and ChatGPT and Perplexity cite it. Claim your listing to get a Featured badge, top placement in your category, and a permanent dofollow backlink — from $19/mo, cancel anytime.

Frequently Asked Questions

Is LlamaIndex better than Mastra?

It depends on your needs. LlamaIndex offers 8 key features including Document loaders for 100+ formats (PDF, Word, Notion, Confluence) and Advanced chunking and indexing strategies, while Mastra provides 6 features including Agents, tools, and workflows as TypeScript primitives and Built-in observability: traces, metrics, and logs. LlamaIndex uses a open-source model with a free tier, while Mastra is freemium with free access available. Choose based on which features and pricing model align with your requirements.

Is LlamaIndex cheaper than Mastra?

Both tools are similarly priced, starting at $97/month. Both tools offer free tiers, so you can try each before committing. Always check the official websites for the most current pricing.

Can I use LlamaIndex and Mastra together?

Yes, many users combine LlamaIndex and Mastra in their workflow. LlamaIndex excels at document loaders for 100+ formats (pdf, word, notion, confluence), while Mastra shines with agents, tools, and workflows as typescript primitives. Using both allows you to leverage the strengths of each tool, though this means managing two subscriptions — though free tiers can help manage costs.

What's the main difference between LlamaIndex and Mastra?

LlamaIndex is primarily a coding & development tool focused on leading data framework for llms — rag, document q&a, and knowledge retrieval, while Mastra focuses on ai agent infrastructure with typescript agent framework with observability, evals, and cloud deployment, from the creators of gatsby. They serve different primary use cases despite being alternatives.

Learn More

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