Skip to main content
aitoolsatlas.ai
BlogAbout

Explore

  • All Tools
  • Comparisons
  • Best For Guides
  • Blog

Company

  • About
  • Contact
  • Editorial Policy

Legal

  • Privacy Policy
  • Terms of Service
  • Affiliate Disclosure
Privacy PolicyTerms of ServiceAffiliate DisclosureEditorial PolicyContact

© 2026 aitoolsatlas.ai. All rights reserved.

Find the right AI tool in 2 minutes. Independent reviews and honest comparisons of 880+ AI tools.

  1. Home
  2. Tools
  3. Automation & Workflows
  4. Dify
  5. Pricing
OverviewPricingReviewWorth It?Free vs PaidDiscountAlternativesComparePros & ConsIntegrationsTutorialChangelogSecurityAPI
← Back to Dify Overview

Dify Pricing & Plans 2026

Complete pricing guide for Dify. Compare all plans, analyze costs, and find the perfect tier for your needs.

Try Dify Free →Compare Plans ↓

Not sure if free is enough? See our Free vs Paid comparison →
Still deciding? Read our full verdict on whether Dify is worth it →

🆓Free Tier Available
💎4 Paid Plans
⚡No Setup Fees

Choose Your Plan

Sandbox (Free)

$0

mo

  • ✓Free cloud tier with limited message credits, a small number of apps and team members, basic knowledge base and workflow capabilities, suitable for evaluation and personal projects
Start Free Trial →

Professional

Starts around $59/month

mo

  • ✓Higher message and document quotas, more apps and team seats, expanded knowledge base storage, log retention, API rate limit increases, and standard support
Start Free Trial →
Most Popular

Team

Starts around $159/month

mo

  • ✓Larger team collaboration features, additional seats, higher quotas across messages, documents, and storage, plus advanced workflow and annotation tools
Start Free Trial →

Enterprise

Custom pricing

mo

  • ✓Dedicated deployment, SSO/SAML, advanced RBAC, audit logs, priority support, SLA, on-premise/private cloud installation, and custom integrations
Contact Sales →

Self-Hosted (Community)

Free (open source)

mo

  • ✓Full Dify Community Edition deployable via Docker Compose or Kubernetes with no per-message fees—infrastructure and model API costs are paid directly to the underlying providers
Start Free →

Pricing sourced from Dify · Last verified March 2026

Feature Comparison

FeaturesSandbox (Free)ProfessionalTeamEnterpriseSelf-Hosted (Community)
Free cloud tier with limited message credits, a small number of apps and team members, basic knowledge base and workflow capabilities, suitable for evaluation and personal projects✓✓✓✓✓
Higher message and document quotas, more apps and team seats, expanded knowledge base storage, log retention, API rate limit increases, and standard support—✓✓✓✓
Larger team collaboration features, additional seats, higher quotas across messages, documents, and storage, plus advanced workflow and annotation tools——✓✓✓
Dedicated deployment, SSO/SAML, advanced RBAC, audit logs, priority support, SLA, on-premise/private cloud installation, and custom integrations———✓✓
Full Dify Community Edition deployable via Docker Compose or Kubernetes with no per-message fees—infrastructure and model API costs are paid directly to the underlying providers————✓

Is Dify Worth It?

✅ Why Choose Dify

  • • Open-source under a permissive license with full self-hosting support via Docker and Kubernetes, giving teams complete control over data, models, and infrastructure
  • • Visual workflow builder dramatically lowers the barrier for non-engineers to design multi-step agents, RAG pipelines, and chatbots without writing orchestration code
  • • Model-agnostic gateway supports hundreds of providers including OpenAI, Anthropic, Gemini, Mistral, and local models via Ollama or vLLM, enabling provider switching without rewrites
  • • Integrated RAG engine handles ingestion, chunking, embedding, hybrid retrieval, and reranking out of the box, removing the need to stitch together a separate vector stack
  • • Built-in LLMOps features—prompt versioning, logging, annotation, and analytics—provide production observability that most open-source frameworks omit
  • • Extensible plugin and tool marketplace lets agents call external APIs, databases, and SaaS systems with minimal custom code

⚠️ Consider This

  • • Self-hosted deployments can be resource-intensive and require Docker, Kubernetes, and database operational expertise to run reliably at scale
  • • Visual workflow abstraction can become unwieldy for very complex agent logic, where pure code (LangGraph, custom Python) offers finer control and better version diffing
  • • Cloud pricing tiers can escalate quickly for high-volume teams, pushing larger workloads toward self-hosting which adds operational overhead
  • • Documentation and community support, while active, occasionally lag behind rapid feature releases, leaving edge-case behavior under-documented
  • • Some advanced enterprise features such as SSO, fine-grained RBAC, and audit logs are gated behind paid or enterprise plans

What Users Say About Dify

👍 What Users Love

  • ✓Open-source under a permissive license with full self-hosting support via Docker and Kubernetes, giving teams complete control over data, models, and infrastructure
  • ✓Visual workflow builder dramatically lowers the barrier for non-engineers to design multi-step agents, RAG pipelines, and chatbots without writing orchestration code
  • ✓Model-agnostic gateway supports hundreds of providers including OpenAI, Anthropic, Gemini, Mistral, and local models via Ollama or vLLM, enabling provider switching without rewrites
  • ✓Integrated RAG engine handles ingestion, chunking, embedding, hybrid retrieval, and reranking out of the box, removing the need to stitch together a separate vector stack
  • ✓Built-in LLMOps features—prompt versioning, logging, annotation, and analytics—provide production observability that most open-source frameworks omit
  • ✓Extensible plugin and tool marketplace lets agents call external APIs, databases, and SaaS systems with minimal custom code

👎 Common Concerns

  • ⚠Self-hosted deployments can be resource-intensive and require Docker, Kubernetes, and database operational expertise to run reliably at scale
  • ⚠Visual workflow abstraction can become unwieldy for very complex agent logic, where pure code (LangGraph, custom Python) offers finer control and better version diffing
  • ⚠Cloud pricing tiers can escalate quickly for high-volume teams, pushing larger workloads toward self-hosting which adds operational overhead
  • ⚠Documentation and community support, while active, occasionally lag behind rapid feature releases, leaving edge-case behavior under-documented
  • ⚠Some advanced enterprise features such as SSO, fine-grained RBAC, and audit logs are gated behind paid or enterprise plans

Pricing FAQ

Is Dify free and open source?

Yes. Dify is released under an open-source license and can be self-hosted at no cost using Docker Compose or Kubernetes. The team also offers a managed cloud service with paid tiers for users who prefer not to manage infrastructure, plus enterprise plans with SSO, advanced RBAC, and SLA support.

Which LLMs and model providers does Dify support?

Dify is model-agnostic and supports hundreds of providers including OpenAI, Anthropic Claude, Google Gemini, Azure OpenAI, AWS Bedrock, Mistral, Cohere, DeepSeek, Qwen, and Llama. It also integrates with locally hosted runtimes such as Ollama, vLLM, LocalAI, and Xinference, allowing fully on-premise deployments.

How does Dify compare to LangChain or LangGraph?

LangChain and LangGraph are code-first Python libraries for building LLM applications, while Dify is a complete platform that wraps similar capabilities behind a visual builder, hosted UI, RAG engine, and observability layer. Teams that want full programmatic control may prefer LangGraph; teams that want a deployable product with less boilerplate typically prefer Dify.

Can Dify handle Retrieval-Augmented Generation (RAG)?

Yes. Dify includes a built-in knowledge base feature that ingests PDFs, Word documents, web pages, and structured data, then handles chunking, embedding, vector storage, hybrid search, and reranking. Knowledge bases can be attached to any chatbot, agent, or workflow without external infrastructure.

Is Dify suitable for production deployments?

Yes. Dify exposes every application as a REST API, supports horizontal scaling on Kubernetes, and includes logging, prompt versioning, and analytics for production monitoring. Many companies run customer-facing chatbots and internal copilots on Dify, though teams with strict compliance needs typically choose self-hosted or enterprise tiers.

Ready to Get Started?

AI builders and operators use Dify to streamline their workflow.

Try Dify Now →

More about Dify

ReviewAlternativesFree vs PaidPros & ConsWorth It?Tutorial

Compare Dify Pricing with Alternatives

CrewAI Pricing

Open-source Python framework that orchestrates autonomous AI agents collaborating as teams to accomplish complex workflows. Define agents with specific roles and goals, then organize them into crews that execute sequential or parallel tasks. Agents delegate work, share context, and complete multi-step processes like market research, content creation, and data analysis. Supports 100+ LLM providers through LiteLLM integration and includes memory systems for agent learning. Features 48K+ GitHub stars with active community.

Compare Pricing →

Microsoft AutoGen Pricing

Microsoft's open-source framework for building multi-agent AI systems with asynchronous, event-driven architecture.

Compare Pricing →

LangGraph Pricing

Graph-based workflow orchestration framework for building reliable, production-ready AI agents with deterministic state machines, human-in-the-loop capabilities, and comprehensive observability through LangSmith integration.

Compare Pricing →

Microsoft Semantic Kernel Pricing

SDK for building AI agents with planners, memory, and connectors. - Enhanced AI-powered platform providing advanced capabilities for modern development and business workflows. Features comprehensive tooling, integrations, and scalable architecture designed for professional teams and enterprise environments.

Compare Pricing →