--- title: "BrowserAI vs langchaingo" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/sauravpanda-browserai-vs-tmc-langchaingo" tools: ["sauravpanda-browserai", "tmc-langchaingo"] --- # BrowserAI vs langchaingo *GraphCanon updated Aug 25, 2026* ## Verdict Pick BrowserAI if browserAI runs various local LLMs directly in your browser using TypeScript; pick langchaingo if langChainGo simplifies the integration of Large Language Models into Go projects through easy-to-use APIs and composability. [BrowserAI](https://browserai.dev) reports 1.4k GitHub stars, 138 forks, and 24 open issues, last pushed Jul 21, 2026. [langchaingo](https://tmc.github.io/langchaingo/) has 9.6k stars, 1.1k forks, and 410 open issues, last pushed Jan 11, 2026. Figures are from public GitHub metadata via [BrowserAI's repository](https://github.com/sauravpanda/BrowserAI) and [langchaingo's repository](https://github.com/tmc/langchaingo). | | [BrowserAI](/tools/sauravpanda-browserai.md) | [langchaingo](/tools/tmc-langchaingo.md) | | --- | --- | --- | | Tagline | Run local LLMs like llama, deepseek-distill, kokoro and more inside your browser | LangChain for Go, the easiest way to write LLM-based programs in Go | | Stars | 1,449 | 9,600 | | Forks | 138 | 1,135 | | Open issues | 24 | 410 | | Language | TypeScript | Go | | Adopt for | BrowserAI runs various local LLMs directly in your browser using TypeScript. | LangChainGo simplifies the integration of Large Language Models into Go projects through easy-to-use APIs and composability. | | Persona | - | - | | Runtime | - | - | | License | MIT | MIT | | Categories | Inference & Serving, LLM Frameworks | Developer Tools, LLM Frameworks | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [BrowserAI](/tools/sauravpanda-browserai.md) | [langchaingo](/tools/tmc-langchaingo.md) | | --- | --- | --- | | Maintenance | Steady (60%) | Slowing (36%) | | Days since push | 34d | 208d | | Open issues (now) | 24 | 410 | | Stars delta | +3 (30d) | Unknown | | Open issues delta | 0 (30d) | Unknown | | Full report | [trust report](/tools/sauravpanda-browserai/trust.md) | [trust report](/tools/tmc-langchaingo/trust.md) | ## Decision facts: BrowserAI - **Adopt for:** BrowserAI runs various local LLMs directly in your browser using TypeScript. ## 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 BrowserAI if… - BrowserAI is primarily TypeScript; langchaingo is Go. - Tags unique to BrowserAI: agents, llm-inference, local, typescript. - Also covers Inference & Serving. - You need to run local models like llama, deepseek-distill, kokoro inside the browser environment. ### Choose langchaingo if… - langchaingo is primarily Go; BrowserAI is TypeScript. - Tags unique to langchaingo: 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 BrowserAI - You require a server-based solution instead of in-browser execution for LLMs. - The project involves extensive training tasks that are unsuitable for browser environments. ## 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 BrowserAI and langchaingo? BrowserAI: Run local LLMs like llama, deepseek-distill, kokoro and more inside your browser. 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 BrowserAI over langchaingo? Choose BrowserAI over langchaingo when BrowserAI is primarily TypeScript; langchaingo is Go; Tags unique to BrowserAI: agents, llm-inference, local, typescript; Also covers Inference & Serving; You need to run local models like llama, deepseek-distill, kokoro inside the browser environment. ### When should I choose langchaingo over BrowserAI? Choose langchaingo over BrowserAI when langchaingo is primarily Go; BrowserAI is TypeScript; Tags unique to langchaingo: 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 BrowserAI? You require a server-based solution instead of in-browser execution for LLMs. The project involves extensive training tasks that are unsuitable for browser environments. ### 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 BrowserAI or langchaingo more popular on GitHub? langchaingo has more GitHub stars (9,600 vs 1,449). Stars measure visibility, not whether either tool fits your constraints. ### Are BrowserAI and langchaingo open source? Yes - both are open-source projects on GitHub (BrowserAI: MIT, langchaingo: MIT). ### Where can I find alternatives to BrowserAI or langchaingo? GraphCanon lists graph-backed alternatives at [BrowserAI alternatives](/tools/sauravpanda-browserai/alternatives) and [langchaingo alternatives](/tools/tmc-langchaingo/alternatives) ([BrowserAI markdown twin](/tools/sauravpanda-browserai/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/sauravpanda-browserai-vs-tmc-langchaingo.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, BrowserAI or langchaingo? BrowserAI: Steady. 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 BrowserAI and langchaingo? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [BrowserAI trust report](/tools/sauravpanda-browserai/trust); [langchaingo trust report](/tools/tmc-langchaingo/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=sauravpanda-browserai`](/api/graphcanon/graph?tool=sauravpanda-browserai) - 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/_