--- title: "langchain vs langchaingo" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/langchain-ai-langchain-vs-tmc-langchaingo" tools: ["langchain-ai-langchain", "tmc-langchaingo"] --- # langchain vs langchaingo *GraphCanon updated Jul 17, 2026* ## Verdict Pick langchain if 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; pick langchaingo if langChainGo simplifies the integration of Large Language Models into Go projects through easy-to-use APIs and composability. [langchain](https://docs.langchain.com/langchain/) reports 142k GitHub stars, 24k forks, and 419 open issues, last pushed Jul 14, 2026. [langchaingo](https://tmc.github.io/langchaingo/) has 9.5k stars, 1.1k forks, and 404 open issues, last pushed Jan 11, 2026. Figures are from public GitHub metadata via [langchain's repository](https://github.com/langchain-ai/langchain) and [langchaingo's repository](https://github.com/tmc/langchaingo). | | [langchain](/tools/langchain-ai-langchain.md) | [langchaingo](/tools/tmc-langchaingo.md) | | --- | --- | --- | | Tagline | The agent engineering platform. | LangChain for Go, the easiest way to write LLM-based programs in Go | | Stars | 141,713 | 9,538 | | Forks | 23,545 | 1,118 | | Open issues | 419 | 404 | | Language | Python | Go | | 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 | LangChainGo simplifies the integration of Large Language Models into Go projects through easy-to-use APIs and composability. | | Persona | - | - | | Runtime | - | - | | License | MIT License, allowing free use for both personal and commercial purposes under its stipulated terms. | MIT | | Categories | AI Agents, LLM Frameworks | Developer Tools, LLM Frameworks | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [langchain](/tools/langchain-ai-langchain.md) | [langchaingo](/tools/tmc-langchaingo.md) | | --- | --- | --- | | Maintenance | Very active (96%) | Slowing (36%) | | Days since push | 0d | 184d | | Open issues (now) | 419 | 404 | | Owner type | Organization | User | | Full report | [trust report](/tools/langchain-ai-langchain/trust.md) | [trust report](/tools/tmc-langchaingo/trust.md) | **Typed relationship:** langchain _(alternative)_ langchaingo LangChainGo provides LangChain functionality in Go language, which is an alternative platform for LLM-powered applications. ## Shared compatibility - **LangChain**: [langchain](/tools/langchain-ai-langchain.md) - LangChain integration; [langchaingo](/tools/tmc-langchaingo.md) - LangChain integration ## 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. ## Decision facts: langchaingo - **Adopt for:** LangChainGo simplifies the integration of Large Language Models into Go projects through easy-to-use APIs and composability. ## Choose when ### Choose langchain if… - langchain is primarily Python; langchaingo is Go. - 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.. - LangChainGo provides LangChain functionality in Go language, which is an alternative platform for LLM-powered applications. - Tags unique to langchain: agents, ai-agents, anthropic, chatgpt. - Also covers AI Agents. - * When aiming to build complex AI-powered agents or applications requiring high-level capabilities like planning, subagent interaction, and file system operations. ### Choose langchaingo if… - langchaingo is primarily Go; langchain is Python. - LangChainGo provides LangChain functionality in Go language, which is an alternative platform for LLM-powered applications. - Tags unique to langchaingo: ai, go, golang, langchain. - Also covers Developer Tools. - - You are working on a project that requires LLM-based capabilities, but prefer to code in Go. ## 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 langchaingo - - If your project strictly adheres to another programming language where other implementations of LangChain are available. - - When your application requires heavy customization at the framework level that might not be directly supported within LangChainGo’s current implementation. ## Common questions ### What is the difference between langchain and langchaingo? langchain: The agent engineering platform.. langchaingo: LangChain for Go, the easiest way to write LLM-based programs in Go. See the comparison table for live GitHub stats and shared categories. ### When should I choose langchain over langchaingo? Choose langchain over langchaingo when langchain is primarily Python; langchaingo is Go; 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.; LangChainGo provides LangChain functionality in Go language, which is an alternative platform for LLM-powered applications; Tags unique to langchain: agents, ai-agents, anthropic, chatgpt; Also covers AI Agents; * 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 langchaingo over langchain? Choose langchaingo over langchain when langchaingo is primarily Go; langchain is Python; LangChainGo provides LangChain functionality in Go language, which is an alternative platform for LLM-powered applications; Tags unique to langchaingo: ai, go, golang, langchain; Also covers Developer Tools; - You are working on a project that requires LLM-based capabilities, but prefer to code in Go. ### 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 langchaingo? - If your project strictly adheres to another programming language where other implementations of LangChain are available. - When your application requires heavy customization at the framework level that might not be directly supported within LangChainGo’s current implementation. ### Is langchain or langchaingo more popular on GitHub? langchain has more GitHub stars (141,713 vs 9,538). Stars measure visibility, not whether either tool fits your constraints. ### Are langchain and langchaingo open source? Yes - both are open-source projects on GitHub (langchain: MIT, langchaingo: MIT). ### Where can I find alternatives to langchain or langchaingo? GraphCanon lists graph-backed alternatives at [langchain alternatives](/tools/langchain-ai-langchain/alternatives) and [langchaingo alternatives](/tools/tmc-langchaingo/alternatives) ([langchain markdown twin](/tools/langchain-ai-langchain/alternatives.md), [langchaingo markdown twin](/tools/tmc-langchaingo/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-tmc-langchaingo.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, langchain or langchaingo? langchain: Very active. langchaingo: Slowing. 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 langchaingo? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [langchain trust report](/tools/langchain-ai-langchain/trust); [langchaingo trust report](/tools/tmc-langchaingo/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/_