§ Comparison · Updated May 2026

Dify vs Agno.

Dify and Agno are frequently shortlisted together. Both compete in the ai agents space, so the right pick comes down to pricing model, ecosystem, and the specific features you'll lean on. This page lays out the spec sheet, an editor verdict, and answers to the questions people search before choosing.

§ Verdict

Highest rated

Dify

Editor score 4.5/5 — leads on overall quality across our evaluation.

Best value

Agno

open-source and self-hostable pricing — the lowest-friction option of the group.

Broadest feature set

Dify

5 headline features — the most all-in-one option.

OSS / self-host

Agno

Open-source — the only option in this group you can self-host or fork.

§ Spec sheet

Rating

Dify

4.5

Agno

4.1

Pricing

Dify

Freemium

Agno

Open source

Category

Dify

AI Agents

Agno

AI Agents

Features

Dify

• Visual agent and workflow builder
• RAG and knowledge bases
• Multi-model support
• API and embed deployment
• Self-hosting option

Agno

• Pure Python agent framework
• Built-in memory and knowledge
• Production monitoring tools
• Pre-built agent templates
• Multi-model support

Pros

Dify

+ Fast path from prototype to deployed app
+ Strong open-source community and templates

Agno

+ Clean Pythonic API
+ Production-focused features
+ Good starter templates

Cons

Dify

− Self-hosting requires ops effort
− Less polished than single-vendor SaaS for non-technical users

Agno

− Smaller community than LangChain
− Less documentation
− Fewer integrations

Use Cases

Dify

Internal AI assistantsCustomer support botsRAG over company docsAgent prototyping

Agno

Building production AI agentsKnowledge-base powered assistantsMulti-tool AI workflowsEnterprise agent deployment

Visit

Dify

Agno

	Dify Open-source LLM app platform for building agents, RAG apps, and workflows.	Agno Production-grade framework and runtime for building and operating multi-agent systems.
Rating	4.5	4.1
Pricing	Freemium	Open source
Category	AI Agents	AI Agents
Features	• Visual agent and workflow builder • RAG and knowledge bases • Multi-model support • API and embed deployment • Self-hosting option	• Pure Python agent framework • Built-in memory and knowledge • Production monitoring tools • Pre-built agent templates • Multi-model support
Pros	+ Fast path from prototype to deployed app + Strong open-source community and templates	+ Clean Pythonic API + Production-focused features + Good starter templates
Cons	− Self-hosting requires ops effort − Less polished than single-vendor SaaS for non-technical users	− Smaller community than LangChain − Less documentation − Fewer integrations
Use Cases	Internal AI assistantsCustomer support botsRAG over company docsAgent prototyping	Building production AI agentsKnowledge-base powered assistantsMulti-tool AI workflowsEnterprise agent deployment
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§ Best for

Pick Dify for

Developers who need internal ai assistants.

Read full review →

Pick Agno for

Python developers who need building production ai agents.

Read full review →

§ Common questions

Dify vs Agno — which is better?

It depends on what you're optimizing for. Dify edges Agno on our editor rating (4.5 vs 4.1), but ratings are a coarse signal. The verdict above breaks down which one wins for budget, feature breadth, and self-hosting.

Are these tools free?

Yes — every tool here has a free or freemium tier. The differences are in usage limits, advanced features, and how aggressive each free tier is.

When should I pick Dify over Agno?

Pick Dify when internal ai assistants matters more than Agno's strengths in building production ai agents. The "best for" callouts above translate this into concrete personas.

Are there other tools to consider?

Yes — every tool in this comparison has its own alternatives page that ranks the closest competitors. Click any tool name to drill into its full review and alternatives list.

Editorial verdicts, not algorithmicDisagree? Tell us →