langchain vs browser-use
Two of the top projects in Agent frameworks and SDKs, side by side: who leads on each score part and who each one suits, then setup, license, activity and what each review found.
langchain
Python framework for building LLM agents and apps from interoperable components
browser-use
Python library that lets an LLM agent control a web browser
Verdict
langchain ranks higher, 88 to 83. Of the 4 score parts we measure for both, langchain leads on 2, browser-use on 1 and 1 is even.
- Adoptionlangchain leads by 18 points, 97 to 79: a wide gap.
- FreshnessEven at 100.
- Maintenancelangchain leads by 10 points, 86 to 76.
- Agent-readybrowser-use leads by 40 points, 70 to 30: a wide gap.
Pick langchain if you are
Python developers building LLM agents and applications in code
- Common interface across model providers, embeddings and vector stores
- Large integrations library covering tools, retrievers and vector stores
Pick browser-use if you are
Developers building browser-automating agents in Python
- Works with a local Chrome profile, a cloud browser, or a remote browser over CDP
- Custom tools register with a decorator; system prompt can be extended or overridden
| What we compare | langchain | browser-use |
|---|---|---|
| Score parts, out of 100 | ||
| Adoption | 97, widely used | 79, popular |
| Freshness | 100, active | 100, active |
| Maintenance | 86, healthy | 76, fair |
| Easy to run | Not scored for this kind | Not scored for this kind |
| Agent-ready | 30, minimal | 70, partly |
| Facts from GitHub and the README | ||
| Stars | 147.8k | 117.8k |
| License | MIT (permissive) | MIT (permissive) |
| Last commit | Oct 2026 | Oct 2026 |
| Last release | Oct 2026 | Oct 2026 |
| Language | Python | Python |
| Docker | No | Yes |
| GPU | Not stated | Optional |
| arm64 or Apple Silicon | Not stated | Not stated |
langchain
LangChain is a Python library that gives a standard interface to chat models, embeddings, vector stores and tools, so providers can be swapped with little code change. Models load through init_chat_model with a provider:model string. For lower-level agent orchestration it points to LangGraph, and for tracing and evals to LangSmith.
Who it is for: Python developers building LLM agents and applications in code
Strengths
- Common interface across model providers, embeddings and vector stores
- Large integrations library covering tools, retrievers and vector stores
- Companions: LangGraph for orchestration, Deep Agents for planning and subagents
- MIT license; JS/TS counterpart available as LangChain.js
Weaknesses
- Observability, evals and managed deployment sit in LangSmith, a separate product
- Controllable stateful agent workflows need LangGraph, not core LangChain
- README gives no hardware requirements or list of supported providers
- Abstraction layer is another API to learn on top of provider SDKs
- Needs Model provider API or other model backend
- Models: OpenAI (README example), Other providers via integrations
browser-use
Browser Use runs an LLM-driven agent that opens a browser, reads pages and completes tasks such as searching, filling forms and booking slots. It is used as a Python library (3.11+), as a CLI skill for agents like Claude Code, or through a hosted cloud API. It works with OpenAI, Anthropic, Google, Ollama and its own BU2 model, on local or cloud browsers.
Who it is for: Developers building browser-automating agents in Python
Strengths
- Works with a local Chrome profile, a cloud browser, or a remote browser over CDP
- Custom tools register with a decorator; system prompt can be extended or overridden
- Supports OpenAI, Anthropic and Google wrappers, plus local models via Ollama
- Ships a CLI skill so existing coding agents can drive a browser
Weaknesses
- README recommends BU2, which needs a paid Browser Use API key
- CAPTCHA and stealth handling rely on the paid cloud browser, with no guarantee
- Profile sync copies cookies only, not local storage, IndexedDB or extensions
- Hardware needs for local models are not stated in the README
- GPU optional
- Docker
- Needs Python >= 3.11, Chromium-based browser, LLM provider API key or Ollama, Browser Use API key (optional)
- Models: OpenAI, Anthropic, Google, Ollama, BU2 (ChatBrowserUse)
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