--- title: "FastChat vs langcorn" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/lm-sys-fastchat-vs-msoedov-langcorn" tools: ["lm-sys-fastchat", "msoedov-langcorn"] --- # FastChat vs langcorn *GraphCanon updated Aug 21, 2026* ## Verdict Pick FastChat if fastChat is a comprehensive open platform for managing large language models (LLMs) that includes capabilities for training, serving, evaluating, and comparing chatbot models via web UIs and RESTful APIs. It powers ChatB; pick langcorn if langCorn is a tool that serves LangChain LLM apps and agents with FastApi. [FastChat](https://github.com/lm-sys/FastChat) reports 40k GitHub stars, 4.8k forks, and 1.0k open issues, last pushed May 1, 2026. [langcorn](https://langcorn.vercel.app/docs) has 938 stars, 69 forks, and 21 open issues, last pushed Jul 15, 2024. Figures are from public GitHub metadata via [FastChat's repository](https://github.com/lm-sys/FastChat) and [langcorn's repository](https://github.com/msoedov/langcorn). | | [FastChat](/tools/lm-sys-fastchat.md) | [langcorn](/tools/msoedov-langcorn.md) | | --- | --- | --- | | Tagline | An open platform for training, serving, and evaluating large language models | Serving LangChain LLM apps and agents automagically with FastApi | | Stars | 39,517 | 938 | | Forks | 4,788 | 69 | | Open issues | 1,038 | 21 | | Language | Python | Python | | Adopt for | FastChat is a comprehensive open platform for managing large language models (LLMs) that includes capabilities for training, serving, evaluating, and comparing chatbot models via web UIs and RESTful APIs. It powers ChatB | LangCorn is a tool that serves LangChain LLM apps and agents with FastApi. | | Persona | - | - | | Runtime | - | - | | License | Apache-2.0 | MIT | | Categories | Evaluation & Observability, Inference & Serving, LLM Frameworks, Model Training | Inference & Serving | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [FastChat](/tools/lm-sys-fastchat.md) | [langcorn](/tools/msoedov-langcorn.md) | | --- | --- | --- | | Maintenance | Slowing (36%) | Dormant (18%) | | Days since push | 98d | 766d | | Open issues (now) | 1.0k | 21 | | Stars delta | Unknown | 0 (30d) | | Open issues delta | Unknown | 0 (30d) | | Owner type | Organization | User | | Full report | [trust report](/tools/lm-sys-fastchat/trust.md) | [trust report](/tools/msoedov-langcorn/trust.md) | ## Shared compatibility - **Python**: [FastChat](/tools/lm-sys-fastchat.md) - Python runtime; [langcorn](/tools/msoedov-langcorn.md) - Python runtime ## Decision facts: FastChat - **Adopt for:** FastChat is a comprehensive open platform for managing large language models (LLMs) that includes capabilities for training, serving, evaluating, and comparing chatbot models via web UIs and RESTful APIs. It powers ChatB ## Decision facts: langcorn - **Adopt for:** LangCorn is a tool that serves LangChain LLM apps and agents with FastApi. ## Choose when ### Choose FastChat if… - License: FastChat is Apache-2.0, langcorn is MIT. - Tags unique to FastChat: chatbots, distributed-serving, evaluation system. - Also covers Evaluation & Observability, LLM Frameworks, Model Training. - - You are looking to train and evaluate state-of-the-art models such as Vicuna or MT-Bench. ### Choose langcorn if… - License: langcorn is MIT, FastChat is Apache-2.0. - Tags unique to langcorn: api, fastapi, langchain, llm. - When you are deploying applications built with Large Language Models (LLMs) like OpenAI. ## When NOT to use FastChat - - You require a proprietary or closed-source framework; FastChat is open-source under Apache-2.0 license and its use might be unsuitable for environments requiring proprietary solutions. - - Your chatbot evaluation needs do not align with the types of data used in FastChat's datasets (e.g., human votes, MT-Bench evaluations). - - You prefer a more user-friendly setup without the need to clone a repository and manually install dependencies; FastChat requires installation from source with additional steps for Rust and CMake on - + Mac. ## When NOT to use langcorn - When you require a framework other than FastAPI for your deployment needs. - If you are looking for broader support beyond LangChain-compatible projects. - In cases where minimal integration with the current infrastructure is not acceptable, as LangCorn requires specific adaptation steps. ## Common questions ### What is the difference between FastChat and langcorn? FastChat: An open platform for training, serving, and evaluating large language models. langcorn: Serving LangChain LLM apps and agents automagically with FastApi. See the comparison table for live GitHub stats and shared categories. ### When should I choose FastChat over langcorn? Choose FastChat over langcorn when License: FastChat is Apache-2.0, langcorn is MIT; Tags unique to FastChat: chatbots, distributed-serving, evaluation system; Also covers Evaluation & Observability, LLM Frameworks, Model Training; - You are looking to train and evaluate state-of-the-art models such as Vicuna or MT-Bench. ### When should I choose langcorn over FastChat? Choose langcorn over FastChat when License: langcorn is MIT, FastChat is Apache-2.0; Tags unique to langcorn: api, fastapi, langchain, llm; When you are deploying applications built with Large Language Models (LLMs) like OpenAI. ### When should I avoid FastChat? - You require a proprietary or closed-source framework; FastChat is open-source under Apache-2.0 license and its use might be unsuitable for environments requiring proprietary solutions. - Your chatbot evaluation needs do not align with the types of data used in FastChat's datasets (e.g., human votes, MT-Bench evaluations). - You prefer a more user-friendly setup without the need to clone a repository and manually install dependencies; FastChat requires installation from source with additional steps for Rust and CMake on + Mac. ### When should I avoid langcorn? When you require a framework other than FastAPI for your deployment needs. If you are looking for broader support beyond LangChain-compatible projects. In cases where minimal integration with the current infrastructure is not acceptable, as LangCorn requires specific adaptation steps. ### Is FastChat or langcorn more popular on GitHub? FastChat has more GitHub stars (39,517 vs 938). Stars measure visibility, not whether either tool fits your constraints. ### Are FastChat and langcorn open source? Yes - both are open-source projects on GitHub (FastChat: Apache-2.0, langcorn: MIT). ### Where can I find alternatives to FastChat or langcorn? GraphCanon lists graph-backed alternatives at [FastChat alternatives](/tools/lm-sys-fastchat/alternatives) and [langcorn alternatives](/tools/msoedov-langcorn/alternatives) ([FastChat markdown twin](/tools/lm-sys-fastchat/alternatives.md), [langcorn markdown twin](/tools/msoedov-langcorn/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/lm-sys-fastchat-vs-msoedov-langcorn.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, FastChat or langcorn? FastChat: Slowing. langcorn: Dormant. 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 FastChat and langcorn? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [FastChat trust report](/tools/lm-sys-fastchat/trust); [langcorn trust report](/tools/msoedov-langcorn/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=lm-sys-fastchat`](/api/graphcanon/graph?tool=lm-sys-fastchat) - 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/_