THE COMPARISON / A CLOSER LOOK

Agno vs LlamaIndex

Compare the listed plans, useful capabilities, and practical tradeoffs.

Prices and features reflect editorial records. Check vendor terms before you buy; documentary checks do not imply hands-on testing.

Agno

🔴Developer

Agent Framework

High-performance Python agent framework designed for multi-agent systems and production workloads with microsecond agent instantiation.

SOURCE-CHECK COVERAGE

No scoped source-check record shown. Check current pricing and vendor terms before buying.

Starting Price

Free

LlamaIndex

🔴Developer

Knowledge agents

A framework and managed platform for building agents over documents and enterprise data.

SOURCE-CHECK COVERAGE

No scoped source-check record shown. Check current pricing and vendor terms before buying.

Starting Price

Free

Feature Comparison

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FeatureAgnoLlamaIndex
CategoryAgent FrameworkKnowledge agents
Pricing Plans3 listed plans4 listed plans
Starting PriceFreeFree
Key Features
  • • Agent, team, and workflow building primitives
  • • AgentOS production runtime with FastAPI backend
  • • Control Plane for monitoring and management
  • • LlamaParse for 50+ unstructured file types
  • • Document parsing, extraction, indexing, and retrieval
  • • Open-source repos plus LiteParse for local document parsing

Agno - Pros & Cons

Pros

  • ✓Genuinely faster agent instantiation and lower memory than LangChain or CrewAI in published benchmarks
  • ✓Self-hostable end-to-end (framework + AgentOS + Control Plane on the paid tier) — no data leaves your infrastructure
  • ✓Native MCP client with a clean, single-line integration path
  • ✓Documentation and copy-runnable examples are unusually good for an open-source agent framework
  • ✓One coherent API for single agents, multi-agent Teams, and deterministic Workflows

Cons

  • ✗Python-only — no first-class TypeScript SDK
  • ✗Smaller ecosystem than LangChain (fewer third-party integrations, tutorials, and Stack Overflow answers)
  • ✗No fully-hosted SaaS runtime yet — you have to run AgentOS yourself or pay $150/mo for the Control Plane on top
  • ✗The rapid renaming from Phidata to Agno left some outdated docs and blog posts in search results
  • ✗Advanced multi-agent patterns still require reading examples; visual builder is not the focus

LlamaIndex - Pros & Cons

Pros

  • ✓Best-in-class retrieval strategies: hybrid, parent-child, summary indexes, knowledge graphs
  • ✓LlamaParse is the strongest PDF/document parser for enterprise RAG today
  • ✓Open-source library is MIT-licensed and runs anywhere
  • ✓Workflows agent layer is a clean alternative to LangGraph for stateful task graphs
  • ✓10,000 free LlamaCloud credits make evaluation painless

Cons

  • ✗LlamaCloud paid pricing is credit-based and harder to model than seat pricing
  • ✗Workflows ecosystem is younger than LangGraph's; fewer multi-agent examples in the wild
  • ✗Library API has churned over major releases — older tutorials are often out of date
  • ✗Visual builder UX is not part of the product; teams that want no-code go elsewhere
  • ✗Pure agent orchestration with complex branching is still cleaner in LangGraph

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🔒 Security & Compliance Comparison

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Security FeatureAgnoLlamaIndex
SOC2❌ No—
GDPR✅ Yes—
HIPAA❌ No—
SSO✅ Yes🏢 Enterprise
Self-Hosted✅ Yes🔀 Hybrid
On-Prem✅ Yes—
RBAC✅ Yes—
Audit Log✅ Yes—
Open Source✅ Yes✅ Yes
API Key Auth✅ Yes✅ Yes
Encryption at Rest✅ Yes—
Encryption in Transit✅ Yes—
Data Residency—not publicly confirmed
Data Retentionconfigurablecached data retained for 48 hours by default for LlamaParse, with caching optional
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