DSPy vs LangChain
Side-by-side comparison with live GitHub signals. Last updated May 16, 2026.
| Metric | DSPy | LangChain |
|---|---|---|
| GitHub Stars | 34.5K | 136.8K |
| Contributors | 393 | 469 |
| Last Commit | May 15, 2026 | May 16, 2026 |
| Open Issues | 474 | 584 |
| License | open-source | open-source |
| Pricing | open-source | open-source |
| Free Tier | Yes | Yes |
| Category | frameworks | frameworks |
| Trending | No | No |
Shared Tags
Only in DSPy
Only in LangChain
About DSPy
DSPy replaces prompt engineering with programming. Instead of writing prompts, you define modules with input/output signatures and DSPy automatically optimizes the prompts and weights for your pipeline. Supports chain-of-thought, retrieval-augmented generation, and multi-hop reasoning patterns. From Stanford NLP.
View full listingAbout LangChain
LangChain is the most widely adopted framework for building LLM-powered applications. It provides modular abstractions for chains, agents, memory, retrievers, and tools, enabling developers to compose complex pipelines from reusable components. Available in both Python and JavaScript/TypeScript, LangChain integrates with every major LLM provider, vector store, and data source. Its ecosystem includes LangSmith for observability and LangGraph for stateful, graph-based agent workflows.
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