Side-by-side comparison
Dify vs LangChain
vs
Side-by-side comparison based on our agenticness evaluation framework
At a glance
Quick Facts
| Feature | Dify | LangChain |
|---|---|---|
| Category | Agent Frameworks & Orchestration | Agent Frameworks & Orchestration |
| Deployment | Hybrid (cloud + self-hosted) | Self-hosted |
| Autonomy Level | Semi-autonomous | Copilot (human-in-loop) |
| Model Support | Multi-model | Multi-model |
| Open Source | Yes | Yes |
| MCP Support | -- | Yes |
| Team Support | Small team | Small team |
| Pricing Model | Free / open source | Free / open source |
| Interface | web, api | api, cli |
36-point evaluation
Agenticness
11/36
Guided Assistant
Dify
10/36
Guided Assistant
LangChain
Dimension Breakdown (0-4 each)
Action Capability
Dify
1
LangChain
2
Autonomy
Dify
1
LangChain
1
Planning
Dify
1
LangChain
1
Adaptation
Dify
1
LangChain
0
State & Memory
Dify
1
LangChain
0
Reliability
Dify
1
LangChain
0
Interoperability
Dify
1
LangChain
2
Safety
Dify
2
LangChain
1
Scores from our agenticness evaluation framework. Higher is more autonomous.
Features & Use Cases
Dify
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
- Publish apps as a web app or API
- App logs and runtime data analysis
- Role management and web app branding customization
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
- A team that needs to publish AI functionality as an API or web app
- An organization that wants to compare model providers in one platform
LangChain
Features
- Python framework for building agents and LLM applications
- Interoperable interfaces for models, embeddings, vector stores, and retrievers
- Third-party integrations for data sources, tools, and model providers
- Modular component-based architecture for composing workflows
- Works with LangGraph for more controllable agent orchestration
- Integrates with LangSmith for debugging, evaluation, and deployment support
- Open-source MIT-licensed codebase
Use Cases
- Building custom AI agents that call tools and external systems
- Prototyping LLM applications before hardening them for production
- Connecting language models to retrieval and data-augmentation workflows
- Swapping model providers while keeping application logic stable
- Developing and debugging agent workflows alongside LangGraph and LangSmith
Pricing
Dify
- **Free / open source** — full functionality available at no cost.
LangChain
- **Free / open source** — full functionality available at no cost.
Analysis
Our Verdict
Choose Dify when the priority is getting a production-oriented AI application into users’ hands through a managed app platform: it provides app types such as chatflows and workflows, document knowledge bases, operational logs, collaboration controls, and direct web-app or API publishing, while allowing either cloud or self-hosted deployment. Choose LangChain when the priority is engineering a deeply custom Python application: its modular interfaces let developers assemble and swap retrieval, model, tool, and external-system components in code, with LangGraph available for tighter orchestration and LangSmith supporting the surrounding development and evaluation workflow.
Choose Dify if...
- +Choose Dify if you want to assemble and operate a chatbot, text generator, agent, chatflow, or workflow through an app platform rather than build the entire experience inside a Python codebase.
- +Choose Dify if your team needs a built-in knowledge base for uploaded documents, plus app logs and runtime-data analysis for a document-retrieval application.
- +Choose Dify if you need to publish the finished AI capability directly as a branded web app or API, with workspace roles and collaboration controls.
- +Choose Dify if cloud hosting is useful now but a self-hosted deployment option is important for later infrastructure control, or if you want to trial multiple providers such as OpenAI, Anthropic, Azure OpenAI, Hugging Face, and Replicate from one platform.
Choose LangChain if...
- +Choose LangChain if you are developing in Python and need code-level control to compose custom multi-step applications from interchangeable models, embeddings, vector stores, retrievers, tools, and external systems.
- +Choose LangChain if your agent must call bespoke tools or connect to specialized data sources and services through its broad integration-oriented component model.
- +Choose LangChain if you need more controllable agent orchestration via LangGraph, rather than a preconfigured app-building workflow environment.
- +Choose LangChain if your engineering workflow benefits from LangSmith’s adjacent debugging, evaluation, and deployment support while you develop and harden agent behavior.