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Dify

Build and run AI apps with cloud or self-hosted deployment

Dify is a platform for creating AI apps, agents, chatflows, and workflows with either a cloud service or self-hosted setup. It offers a free sandbox and paid plans for individuals and teams that need higher usage, more workspaces, and collaboration.

iOS
API
B2B
For Developers
Cloud Hosted
Self-Hosted
Hybrid
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About

What It Is

Dify is an AI app platform for developers and teams building production LLM applications. From the pricing page, it positions itself around app building, RAG pipelines, integrations, observability, and workflow-based agent apps rather than simple chat.

You can use it as a cloud service or deploy it self-hosted. Getting started appears straightforward: sign up for the cloud sandbox or choose a paid workspace plan, with support for multiple model providers including OpenAI, Anthropic, Llama 2, Azure OpenAI, Hugging Face, and Replicate.

What to Know

The platform looks strongest for teams that want a managed way to build and operate AI applications with document handling, logs, and app publishing. The pricing page also suggests meaningful limits by plan, especially around message credits, workspaces, team members, knowledge documents, and API rate limits.

What is less clear from this page is the full extent of the self-hosted edition, the exact pricing for enterprise arrangements, and whether Dify itself is open source under a specific license. It also does not indicate MCP support. If you only need a simple chatbot or a purely consumer-facing assistant, Dify may be more platform than you need; it seems aimed more at builders and teams shipping AI apps.

Key Features
Cloud-hosted and self-hosted deployment options
Free sandbox with 200 message credits
Supports OpenAI, Anthropic, Llama 2, Azure OpenAI, Hugging Face, and Replicate
Builds chatbot, text generator, agent, chatflow, and workflow apps
Knowledge base with document upload and knowledge storage limits
Use Cases
A developer prototyping an AI app with the free sandbox before moving to a paid workspace
A small team building a production chatbot or workflow app with document retrieval
A company that wants a self-hosted option for tighter infrastructure control
Agenticness: Guided Assistant 💬

Executes tasks you assign, one step at a time, within narrow domains.

High evidence
Last evaluated: Mar 28, 2026

Dimension Breakdown

Action Capability
Autonomy
Adaptation
State & Memory
Safety

Categories

Pricing
  • Free: Sandbox plan with 200 message credits, 1 team workspace, 1 team member, 5 apps, 50 knowledge documents, and limited throughput.
  • Professional ($59/workspace/month): 5,000 message credits/month, 3 team members, 50 apps, 500 knowledge documents, and higher limits for workflows and API usage.
  • Team ($159/workspace/month): 10,000 message credits/month, 50 team members, 200 apps, 1,000 knowledge documents, and higher throughput plus unlimited log history.
  • Enterprise: Pricing not publicly listed; contact sales.
Details
AddedMarch 26, 2026
RefreshedMarch 28, 2026
Quick Facts
DeploymentHybrid (cloud + self-hosted)
AutonomySemi-autonomous
Model supportMulti-model
Open sourceYes
Team supportSmall team
Pricing modelFree / open source
Interfaceweb, api

Agent Frameworks & Orchestration

Agent Development Kit (ADK) is a framework for developers building AI agents and multi-agent workflows. It supports Python, TypeScript, Go, and Java, and is designed to run across different models and deployment setups.

API
Integrations
Multi-Agent
+4

Semantic Kernel is Microsoft’s lightweight, open-source framework for adding AI models and agent workflows to C#, Python, and Java applications. It helps developers connect prompts, plugins, memory, and model calls into software that can take actions through existing APIs.

Open Source
iOS
API
+4