Agno vs Dify: Agent Frameworks Comparison
Compare Agno and Dify side by side. Both are tools in the Agent Frameworks category.
Updated April 29, 2026
The short answer
Choose Agno if production-first design with stateless scaling and AgentOS runtime.
Choose Dify if open-source with strong community.
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Quick Comparison
| Category | Agent Frameworks | Agent Frameworks |
| Pricing | Free open-source | Open Source |
| Best For | Python teams building production AI agents that want first-class deployment, observability, and multi-agent support | Technical teams who want a visual builder for AI applications with the option to self-host |
| Website | agno.com | dify.ai |
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Pros & Cons: Agno vs Dify
- +Production-first design with stateless scaling and AgentOS runtime
- +39K+ GitHub stars and 424 active contributors
- +100+ pre-built tools including MCP support
- +Control plane UI is rare in OSS agent frameworks
- +Memory in your DB — no vendor lock-in
- −Newer than LangChain ecosystem — fewer third-party integrations
- −Python-only — no JS/TS SDK
- −Smaller community than LangChain at production scale
- −Less battle-tested at Fortune 500 scale than LangGraph
- +Open-source with strong community
- +Visual workflow builder accelerates development
- +Generous free tier with 200 GPT-4 calls
- +Production-ready platform
- −Pricing details not fully transparent
- −Specific tier costs require contact
- −Taxes excluded from published prices
Pricing: Agno vs Dify
- · Full Python SDK + AgentOS runtime
- · Control plane UI included
- · 100+ tool integrations + MCP
- · Apache 2.0 license
- · 200 free GPT-4 calls
- · Core features
- · Limited resources
- · Community support
- · Independent developers
- · Production applications
- · Increased limits
- · Priority support
- · 10k message credits/month
- · 200 apps
- · 1k knowledge docs
- · 20GB storage
- · Unlimited limits
- · Dedicated support
- · SSO integration
- · Private cloud/VPC
What people are saying
Curated quotes from Hacker News, Reddit, Product Hunt, and review blogs. Dates shown so you can judge whether early criticism still applies.
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“Agno has emerged as one of the fastest-growing AI agent frameworks in 2026 — 39,100+ stars and a 424-contributor community.”
— DecisionCrafters review, DecisionCrafters · Apr 2026 - +
“Purpose-built for production with stateless scaling, session management, and enterprise features — closer to a 'framework + runtime + control plane' than just an SDK.”
— WorkOS engineering blog, WorkOS Blog · Mar 2026 - +
“Memory is stored in your database — you own the data, not the vendor. That alone made it the right call for our compliance posture.”
— Production team review, DecisionCrafters · Mar 2026 - ·
“Smaller community than LangChain at production scale — but the documentation gap is closing fast.”
— Framework comparison, AI Agents Directory · Mar 2026
When to Choose Agno vs Dify
- Production multi-agent systems with stateless scaling
- Customer-facing AI assistants with session management
- Internal-tool agents with monitoring dashboards
- Building AI chatbots without deep coding
- RAG application development
- AI workflow prototyping
How to Choose a Agent Frameworks Tool
Key criteria to evaluate when comparing Agent Frameworks solutions:
About Agno
Agno (formerly Phidata) is an open-source Python framework for building production-grade AI agents and multi-agent systems. With 39,100+ GitHub stars and an active 424-contributor community, it's emerged as one of the fastest-growing agent frameworks in 2026.
Agno provides three integrated layers: a Python SDK for building individual agents and multi-agent teams, a stateless FastAPI runtime called AgentOS for production deployment, and a control plane UI for monitoring, session management, and team operations. It supports 23+ LLM providers (OpenAI, Anthropic Claude, Google Gemini, and more) and ships 100+ pre-built tool integrations including web search, data analysis, file operations, and Model Context Protocol (MCP) servers.
Memory and knowledge systems are first-class: user memories, session memories, and RAG knowledge bases are stored in your database — you own the data, not Agno. Recent v2.5.13 (March 2026) added ReliabilityEval for agent evaluation, enhanced AgentOS APIs for session management, and Slack interface improvements. Agno is positioned as the production-first alternative to LangChain/LangGraph for Python teams.
About Dify
Dify is a production-ready LLMOps platform for agentic workflow development, offering visual tools to build AI-native applications. The Sandbox tier provides 200 free GPT-4 calls, while Professional and Team plans serve independent developers and medium teams respectively. Team plan includes 10,000 message credits monthly with increased limits (200 apps, 1,000 knowledge documents, 20GB storage). Enterprise tier offers custom pricing with unlimited limits, dedicated support, SSO, and private cloud deployment. Dify is open-source and widely adopted for its easy-to-use interface enabling rapid AI application development without extensive coding.
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 Frameworkstools →Frequently Asked Questions
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