Vercel AI SDK vs LangChain / LangGraph
Side-by-side comparison of Vercel AI SDK and LangChain / LangGraph. Pricing, features, best use cases, and honest verdict from a developer who has tested both.
Key Takeaways
- +Vercel AI SDK is better for: ai, framework, typescript
- +LangChain / LangGraph is better for: ai, framework, python
- ~Both are ai frameworks tools. Your choice depends on workflow preference and team setup.
Vercel AI SDK
EssentialThe TypeScript toolkit for building AI apps. Unified API across OpenAI, Anthropic, Google. Streaming, tool calling, structured output, multi-step agents. 50K+ GitHub stars.
LangChain / LangGraph
Most popular LLM framework. 100K+ GitHub stars. Chains, RAG, vector stores, tool use. LangGraph adds stateful multi-agent workflows with cycles and persistence.
Feature Comparison
| Feature | Vercel AI SDK | LangChain / LangGraph |
|---|---|---|
| Category | AI Frameworks | AI Frameworks |
| Type | SDK / Framework | SDK / Framework |
| Pricing | See website for pricing | See website for pricing |
| Best For | TypeScript AI apps with streaming and tool use | RAG, chains, and stateful agent workflows |
| Language / Platform | TypeScript | Python |
| Open Source | No | No |
In Depth
Vercel AI SDK
The Vercel AI SDK is the standard TypeScript library for building AI-powered applications. It provides a unified interface - write code once, swap between OpenAI, Anthropic, Google, or any provider. Key features: streaming chat responses, structured JSON output with Zod schemas, tool calling with automatic execution, and multi-step agent loops. The `ai` core package handles the LLM interaction, `ai/react` provides React hooks (useChat, useCompletion), and `ai/rsc` enables server-side streaming with React Server Components. Over 50K GitHub stars. I use it in nearly every project and built a complete course on it for this site.
LangChain / LangGraph
LangChain is the most popular framework for building LLM applications, with over 100K GitHub stars. It provides abstractions for chains (sequential LLM calls), RAG (retrieval-augmented generation with any vector store), tool use, and output parsing. LangGraph extends it with stateful, graph-based workflows - agents that can loop, branch, and persist state across interactions. Their latest push is 'Deep Agents' for autonomous coding. LangSmith provides observability and tracing. The ecosystem is massive - integrations with every model provider, vector database, and tool imaginable. I cover LangChain in my AI Agent Frameworks course.
The Verdict
Both Vercel AI SDK and LangChain / LangGraph are strong tools in the ai frameworks space. The right choice depends on your workflow. Read the full review of each tool for a deeper dive, or watch the video walkthroughs to see them in action.
