--- title: "langchain vs open-multi-agent" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/langchain-ai-langchain-vs-open-multi-agent-open-multi-agent" tools: ["langchain-ai-langchain", "open-multi-agent-open-multi-agent"] --- # langchain vs open-multi-agent *GraphCanon updated Jul 15, 2026* ## Verdict Pick langchain when langchain is primarily Python; open-multi-agent is TypeScript; pick open-multi-agent when open-multi-agent is primarily TypeScript; langchain is Python. [langchain](https://docs.langchain.com/langchain/) reports 142k GitHub stars, 24k forks, and 419 open issues, last pushed Jul 14, 2026. [open-multi-agent](https://open-multi-agent.com/?utm_source=github) has 6.6k stars, 2.4k forks, and 10 open issues, last pushed Jul 15, 2026. Figures are from public GitHub metadata via [langchain's repository](https://github.com/langchain-ai/langchain) and [open-multi-agent's repository](https://github.com/open-multi-agent/open-multi-agent). | | [langchain](/tools/langchain-ai-langchain.md) | [open-multi-agent](/tools/open-multi-agent-open-multi-agent.md) | | --- | --- | --- | | Tagline | The agent engineering platform. | TypeScript AI agent orchestration framework with dynamic workflows. Describe the goal, not the graph: a coordinator plans the task DAG at runtime and runs it on any LLM (Claude, ChatGPT, Gemini, DeepS | | Stars | 141,713 | 6,581 | | Forks | 23,545 | 2,407 | | Open issues | 419 | 10 | | Language | Python | TypeScript | | Adopt for | LangChain is an open-source platform designed specifically for building agents and applications that leverage large language models (LLMs). It provides a standard framework to develop interoperable components and connect | - | | Persona | - | - | | Runtime | - | - | | License | MIT License, allowing free use for both personal and commercial purposes under its stipulated terms. | MIT | | Categories | AI Agents, LLM Frameworks | AI Agents, Inference & Serving, LLM Frameworks | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [langchain](/tools/langchain-ai-langchain.md) | [open-multi-agent](/tools/open-multi-agent-open-multi-agent.md) | | --- | --- | --- | | Open issues (now) | 419 | 10 | | Full report | [trust report](/tools/langchain-ai-langchain/trust.md) | [trust report](/tools/open-multi-agent-open-multi-agent/trust.md) | ## Decision facts: langchain - **Pricing:** freemium - LangChain itself is open-source and free to use. However, it might rely on paid services or premium models from external platforms like OpenAI. - **Adopt for:** LangChain is an open-source platform designed specifically for building agents and applications that leverage large language models (LLMs). It provides a standard framework to develop interoperable components and connect - **License detail:** MIT License, allowing free use for both personal and commercial purposes under its stipulated terms. ## Choose when ### Choose langchain if… - langchain is primarily Python; open-multi-agent is TypeScript. - Pricing: LangChain itself is open-source and free to use. However, it might rely on paid services or premium models from external platforms like OpenAI.. - Tags unique to langchain: agents, chatgpt, deepagents, enterprise. - * When aiming to build complex AI-powered agents or applications requiring high-level capabilities like planning, subagent interaction, and file system operations. ### Choose open-multi-agent if… - open-multi-agent is primarily TypeScript; langchain is Python. - Tags unique to open-multi-agent: agent-framework, agent-orchestration, agentic-ai, claude. - Also covers Inference & Serving. ## When NOT to use langchain - * When working on smaller, less complex projects where full-scale integration with sophisticated components is not necessary as LangChain's extensive features might introduce unnecessary complexity. - * If you are primarily focused on JavaScript or TypeScript development as the primary focus of LangChain is Python. Although there is a JS/TS equivalent (LangChain.js), it may not offer the same depth - * For projects requiring heavy customization at lower levels, where a more granular control over individual components is required rather than working with an integrated framework. ## When NOT to use open-multi-agent - AI Agents: Don't use an agent loop when a deterministic workflow would do; agents add latency, cost, and non-determinism. - Inference & Serving: Self-hosting rarely beats a hosted API on cost until you have steady, high-volume traffic. - LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves. ## Common questions ### What is the difference between langchain and open-multi-agent? langchain: The agent engineering platform.. open-multi-agent: TypeScript AI agent orchestration framework with dynamic workflows. Describe the goal, not the graph: a coordinator plans the task DAG at runtime and runs it on any LLM (Claude, ChatGPT, Gemini, DeepS. See the comparison table for live GitHub stats and shared categories. ### When should I choose langchain over open-multi-agent? Choose langchain over open-multi-agent when langchain is primarily Python; open-multi-agent is TypeScript; Pricing: LangChain itself is open-source and free to use. However, it might rely on paid services or premium models from external platforms like OpenAI.; Tags unique to langchain: agents, chatgpt, deepagents, enterprise; * When aiming to build complex AI-powered agents or applications requiring high-level capabilities like planning, subagent interaction, and file system operations. ### When should I choose open-multi-agent over langchain? Choose open-multi-agent over langchain when open-multi-agent is primarily TypeScript; langchain is Python; Tags unique to open-multi-agent: agent-framework, agent-orchestration, agentic-ai, claude; Also covers Inference & Serving. ### When should I avoid langchain? * When working on smaller, less complex projects where full-scale integration with sophisticated components is not necessary as LangChain's extensive features might introduce unnecessary complexity. * If you are primarily focused on JavaScript or TypeScript development as the primary focus of LangChain is Python. Although there is a JS/TS equivalent (LangChain.js), it may not offer the same depth * For projects requiring heavy customization at lower levels, where a more granular control over individual components is required rather than working with an integrated framework. ### When should I avoid open-multi-agent? AI Agents: Don't use an agent loop when a deterministic workflow would do; agents add latency, cost, and non-determinism. Inference & Serving: Self-hosting rarely beats a hosted API on cost until you have steady, high-volume traffic. LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves. ### Is langchain or open-multi-agent more popular on GitHub? langchain has more GitHub stars (141,713 vs 6,581). Stars measure visibility, not whether either tool fits your constraints. ### Are langchain and open-multi-agent open source? Yes - both are open-source projects on GitHub (langchain: MIT, open-multi-agent: MIT). ### Where can I find alternatives to langchain or open-multi-agent? GraphCanon lists graph-backed alternatives at [langchain alternatives](/tools/langchain-ai-langchain/alternatives) and [open-multi-agent alternatives](/tools/open-multi-agent-open-multi-agent/alternatives) ([langchain markdown twin](/tools/langchain-ai-langchain/alternatives.md), [open-multi-agent markdown twin](/tools/open-multi-agent-open-multi-agent/alternatives.md)), ranked by typed relationship edges rather than popularity votes. ### Is there a machine-readable version of this comparison? Yes. The markdown twin at [this comparison](/compare/langchain-ai-langchain-vs-open-multi-agent-open-multi-agent.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, langchain or open-multi-agent? langchain: Very active. open-multi-agent: Very active. Compare maintenance labels, days since push, and release cadence in the trust section below - stars alone do not measure maintenance. ### Where are the full trust reports for langchain and open-multi-agent? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [langchain trust report](/tools/langchain-ai-langchain/trust); [open-multi-agent trust report](/tools/open-multi-agent-open-multi-agent/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=langchain-ai-langchain`](/api/graphcanon/graph?tool=langchain-ai-langchain) - LLM index: [/llms.txt](/llms.txt) - Full corpus: [/llms-full.txt](/llms-full.txt) _GraphCanon - The knowledge graph for AI development. https://www.graphcanon.com/_