Dify vs LangSmith
Dify
dify.ai
LangSmith
langchain.comSide by side
| Figure | Dify | LangSmith |
|---|---|---|
| Price from | $49.17/mo | $39/mo |
| Free plan | Yes | Yes |
| Free trial | — | — |
| Open source | Yes | — |
| Web | Yes | Yes |
| Windows | Yes | Yes |
| macOS | Yes | Yes |
| Linux | Yes | Yes |
| API | Yes | Yes |
| Self-hosted | Yes | Yes |
| Plans published | 11 | 3 |
| Spec score · AI Agent Platforms | 9.3 (#1) | 9.0 (#4) |
| Spec score · Ai Agent Automation | 9.2 (#1) | 8.9 (#3) |
| Founded | G2 lists Dify as serving customers since 2023 and gives a 2023 founding year. | 2023 |
| Headquarters | California, United States | San Francisco, California, United States |
| Integrations | The Marketplace provides model providers, tools, data sources, MCP integrations, and reusable plugins, with support for custom definitions. | Documented integrations cover OpenAI, Anthropic, Bedrock, Gemini, Mistral, LiteLLM, OpenTelemetry, CrewAI, Vercel AI SDK, PydanticAI, AutoGen and many other frameworks and providers. |
| Purpose | Dify is an open-source platform for building AI applications with agentic workflows, RAG pipelines, model management, observability, and tools. | LangSmith is a commercial agent engineering platform for building, testing, deploying, monitoring, and improving AI agents. |
| Rating on G2 | 4.1 out of 5 from 20 reviews. | 4.4 out of 5 from 78 reviews. |
| Rating on Gartner Peer Insights | 4.0 out of 5 from 1 rating. | 4.4 out of 5 from 25 ratings. |
| Self-hosting | Community Edition can be deployed with Docker Compose, while Enterprise supports private or VPC deployment and Kubernetes Helm charts. | Enterprise customers can run LangSmith self-hosted or hybrid on Kubernetes in AWS, Google Cloud or Azure. |
| Support | Sandbox support is community and help documentation, while Professional and Team include priority email support. | The Developer plan includes community support, and the Enterprise plan lists a support SLA. |
| System requirements | The Docker deployment requires at least two CPU cores and 4 GiB RAM; supported setups include macOS 10.14+, Linux with Docker 19.03+, and Windows with WSL2. | Agent Server deployments require PostgreSQL and Redis; self-hosted installations may use customer-managed PostgreSQL and Redis. |
| What it does | Dify is an LLM application platform combining visual workflows, RAG pipelines, agents, model and tool support, publishing, and monitoring. | LangSmith is LangChain's framework-agnostic platform for observing, evaluating and deploying AI agents. |
Plans
Dify
- CommunityFree
- CommunityFree
- SandboxFree
- SandboxFree
- Professional$59 a month
- Team$159 a month
- Professional$590 a year
- Professional$590 a year
- Team$1,590 a year
- Team$1,590 a year
In their own words
Dify
Dify is an open-source platform for building AI applications with agentic workflows, retrieval pipelines, model management, observability, and tools. Workflow Studio provides a visual canvas for model calls, knowledge retrieval, tools, code, branching, triggers, and human review. Workflows can start from user input, API calls, schedules, webhooks, plugin events, or uploaded payloads. Knowledge Pipeline turns files, online documents, drives, crawlers, and web content into searchable knowledge bases with metadata and citations. Retrieval supports semantic, keyword, hybrid, and reranked methods with metadata filters. Applications can be published as hosted web apps, website embeds, API endpoints, or MCP servers. Dify connects to providers including OpenAI, Anthropic, Google Gemini, and xAI, while its Marketplace lists more than 200 tools. Community Edition is self-hostable with Docker; Enterprise can run in a customer VPC, on-premises, or an air-gapped network. Sandbox and Community are free. Professional costs $590 a year per workspace; Team costs $1,590 a year per workspace.
LangSmith
LangSmith is a commercial agent-engineering platform for building, evaluating, deploying, monitoring, and improving AI agents. It supports offline evaluations on curated datasets and real-time scoring of production interactions. Evaluation methods include human review, heuristic checks, LLM-as-judge evaluators, pairwise comparisons, and custom Python or TypeScript evaluators. Annotation queues route runs to subject-matter experts for feedback that can calibrate evaluations, improve prompts, or augment datasets. The Playground compares prompt versions or model providers, and LangSmith chat can auto-improve prompts. Observability includes agent and retrieval tracing, token and general cost tracking, trajectory monitoring, online evaluations, and webhook or PagerDuty alerts. Traces can arrive through SDKs or an API from LangGraph, custom Python, or other stacks; SDKs are listed for Python, TypeScript, Go, and Java. Hosting ranges from cloud to hybrid and self-hosted Enterprise options. The Developer plan costs nothing, Plus costs $39 a month, and Enterprise pricing is custom.