--- title: "FastChat vs Server" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/lm-sys-fastchat-vs-rubixml-server" tools: ["lm-sys-fastchat", "rubixml-server"] --- # FastChat vs Server *GraphCanon updated Jul 15, 2026* ## Verdict Pick FastChat when fastChat is primarily Python; Server is PHP; pick Server when server is primarily PHP; FastChat is Python. [FastChat](https://github.com/lm-sys/FastChat) reports 39k GitHub stars, 4.8k forks, and 1.0k open issues, last pushed May 1, 2026. [Server](https://rubixml.github.io/ML) has 63 stars, 13 forks, and 1 open issues, last pushed Mar 3, 2026. Figures are from public GitHub metadata via [FastChat's repository](https://github.com/lm-sys/FastChat) and [Server's repository](https://github.com/RubixML/Server). | | [FastChat](/tools/lm-sys-fastchat.md) | [Server](/tools/rubixml-server.md) | | --- | --- | --- | | Tagline | An open platform for training, serving, and evaluating large language models | A standalone inference server for trained Rubix ML estimators. | | Stars | 39,494 | 63 | | Forks | 4,786 | 13 | | Open issues | 1,027 | 1 | | Language | Python | PHP | | 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 | - | | Persona | - | - | | Runtime | - | - | | License | Apache-2.0 | MIT | | Categories | Evaluation & Observability, Inference & Serving, LLM Frameworks, Model Training | Computer Vision, Inference & Serving, Model Training | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [FastChat](/tools/lm-sys-fastchat.md) | [Server](/tools/rubixml-server.md) | | --- | --- | --- | | Maintenance | Steady (60%) | Slowing (36%) | | Days since push | 74d | 134d | | Open issues (now) | 1.0k | 1 | | Full report | [trust report](/tools/lm-sys-fastchat/trust.md) | [trust report](/tools/rubixml-server/trust.md) | ## 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 ## Choose when ### Choose FastChat if… - FastChat is primarily Python; Server is PHP. - License: FastChat is Apache-2.0, Server is MIT. - Tags unique to FastChat: chatbots, distributed-serving, evaluation system, large-language-models. - Also covers Evaluation & Observability, LLM Frameworks. - - You are looking to train and evaluate state-of-the-art models such as Vicuna or MT-Bench. ### Choose Server if… - Server is primarily PHP; FastChat is Python. - License: Server is MIT, FastChat is Apache-2.0. - Tags unique to Server: api, http-server, inference, inference-engine. - Also covers Computer Vision. ## 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 Server - Last GitHub push was 134 days ago (slowing maintenance, Mar 3, 2026). Validate activity before betting a new project on Server. - Inference & Serving: Self-hosting rarely beats a hosted API on cost until you have steady, high-volume traffic. - Model Training: Try prompting and RAG first; fine-tuning is the answer to style/format, not missing knowledge. ## Common questions ### What is the difference between FastChat and Server? FastChat: An open platform for training, serving, and evaluating large language models. Server: A standalone inference server for trained Rubix ML estimators.. See the comparison table for live GitHub stats and shared categories. ### When should I choose FastChat over Server? Choose FastChat over Server when FastChat is primarily Python; Server is PHP; License: FastChat is Apache-2.0, Server is MIT; Tags unique to FastChat: chatbots, distributed-serving, evaluation system, large-language-models; Also covers Evaluation & Observability, LLM Frameworks; - You are looking to train and evaluate state-of-the-art models such as Vicuna or MT-Bench. ### When should I choose Server over FastChat? Choose Server over FastChat when Server is primarily PHP; FastChat is Python; License: Server is MIT, FastChat is Apache-2.0; Tags unique to Server: api, http-server, inference, inference-engine; Also covers Computer Vision. ### 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 Server? Last GitHub push was 134 days ago (slowing maintenance, Mar 3, 2026). Validate activity before betting a new project on Server. Inference & Serving: Self-hosting rarely beats a hosted API on cost until you have steady, high-volume traffic. Model Training: Try prompting and RAG first; fine-tuning is the answer to style/format, not missing knowledge. ### Is FastChat or Server more popular on GitHub? FastChat has more GitHub stars (39,494 vs 63). Stars measure visibility, not whether either tool fits your constraints. ### Are FastChat and Server open source? Yes - both are open-source projects on GitHub (FastChat: Apache-2.0, Server: MIT). ### Where can I find alternatives to FastChat or Server? GraphCanon lists graph-backed alternatives at [FastChat alternatives](/tools/lm-sys-fastchat/alternatives) and [Server alternatives](/tools/rubixml-server/alternatives) ([FastChat markdown twin](/tools/lm-sys-fastchat/alternatives.md), [Server markdown twin](/tools/rubixml-server/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-rubixml-server.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, FastChat or Server? FastChat: Steady. Server: 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 FastChat and Server? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [FastChat trust report](/tools/lm-sys-fastchat/trust); [Server trust report](/tools/rubixml-server/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/_