Tool A
Agno
High-performance multimodal AI agent framework with native memory and speed
Tool B
LangChain
Build context-aware reasoning applications
Choose this if…
Agno
- 1You need Voice Input
- 2You need Image Output
- 3You need Video Input
- 4Community rates it higher (⭐4.9 vs 4.7)
Choose this if…
LangChain
- 1You need No Signup Required
- 2You want a completely free option
- 3You need power-user and advanced features
Overview
Agno (formerly Phidata) is a lightweight, ultra-fast Python framework engineered for building production-grade autonomous multi-agent systems with native memory, knowledge retrieval, and multimodal reasoning capabilities. It is designed to replace bloated agent frameworks with a pure, pythonic developer experience. Agno agents operate up to 10x faster than legacy orchestration libraries by eliminating unnecessary abstractions. With built-in support for vector databases (PgVector, Qdrant, Pinecone), structured output schemas, and agent-to-agent delegating protocols, developers can build complex autonomous assistants with under 20 lines of clean code.
The framework includes first-class multimodal tools allowing agents to analyze images, process video streams, execute code in secure sandboxes, and query SQL databases. Agno agents natively persist session state and user memory in PostgreSQL, making stateful conversations effortless across web sessions. Agno is fully open-source with extensive documentation, offering enterprise-ready middleware for authentication, telemetry, and rate limiting.
The most popular framework for developing applications powered by large language models, including agents and RAG.
Provides components for memory, data retrieval, and tool usage.
Features Comparison
22 totalPricing & Plans
100% free open-source framework with unlimited local agent execution
Agno Cloud from $29/mo for managed agent deployment, monitoring, and team workspaces
Pros & Cons
Pros
Up to 10x faster execution speed compared to legacy agent libraries
Clean, pythonic syntax with zero unnecessary framework bloat
Native multimodal support for images, video, and audio reasoning
Built-in PostgreSQL memory persistence and vector RAG integration
Completely open source with active developer community
Cons
Primary ecosystem focused on Python (TypeScript SDK in early development)
Migration required for legacy Phidata v1 codebases
Pros
Massive community
Connects to almost any tool
Rapid updates
Cons
Documentation can be dense
Code can become complex
Use Cases
The Verdict
Agno
18/22 features · ⭐4.9
Agno (formerly Phidata) is a lightweight, ultra-fast Python framework engineered for building production-grade autonomous multi-agent systems with native memory…
LangChain
15/22 features · ⭐4.7
The most popular framework for developing applications powered by large language models, including agents and RAG.…
Both Agno and LangChain are capable AI tools serving distinct use cases. Agno leads on raw feature breadth (18 vs 15), making it a stronger choice if you need maximum capability.
Frequently Asked Questions
What is the main difference between Agno and LangChain?
Agno — "High-performance multimodal AI agent framework with native memory and speed" — focuses on agent-ai, code-ai, while LangChain — "Build context-aware reasoning applications" — targets agent-ai, code-ai. The key differences lie in their feature sets and pricing models.
Is Agno free to use?
Yes, Agno offers a free tier. 100% free open-source framework with unlimited local agent execution
Is LangChain free to use?
Yes, LangChain offers a free tier. Open source
Which is better: Agno or LangChain?
It depends on your use case. Agno is rated ⭐4.9 and is best suited for developers, ai-engineers, data-scientists, startups. LangChain is rated ⭐4.7 and is ideal for developers. Use this comparison to evaluate features that matter to your workflow.
Does Agno have an API?
Yes, Agno provides API access for developers and integrations.
More AI Matchups
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