--- title: "FastChat vs VectorHub" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/lm-sys-fastchat-vs-superlinked-vectorhub" tools: ["lm-sys-fastchat", "superlinked-vectorhub"] --- # FastChat vs VectorHub *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 VectorHub if vectorHub hosts Superlinked's deprecated repository for SIE, a self-hosted inference engine designed for embedding generation, OCR, extraction, and document processing tasks. [FastChat](https://github.com/lm-sys/FastChat) reports 40k GitHub stars, 4.8k forks, and 1.0k open issues, last pushed May 1, 2026. [VectorHub](https://superlinked.com/examples/) has 529 stars, 134 forks, and 5 open issues, last pushed Aug 17, 2026. Figures are from public GitHub metadata via [FastChat's repository](https://github.com/lm-sys/FastChat) and [VectorHub's repository](https://github.com/superlinked/VectorHub). | | [FastChat](/tools/lm-sys-fastchat.md) | [VectorHub](/tools/superlinked-vectorhub.md) | | --- | --- | --- | | Tagline | An open platform for training, serving, and evaluating large language models | Deprecated repo for developing SIE, an inference engine for embeddings, reranking, OCR, extraction, and document processing | | Stars | 39,517 | 529 | | Forks | 4,788 | 134 | | Open issues | 1,038 | 5 | | Language | Python | Jupyter Notebook | | 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 | VectorHub hosts Superlinked's deprecated repository for SIE, a self-hosted inference engine designed for embedding generation, OCR, extraction, and document processing tasks. | | Persona | - | - | | Runtime | - | - | | License | Apache-2.0 | Other | | Categories | Evaluation & Observability, Inference & Serving, LLM Frameworks, Model Training | Inference & Serving, Model Training | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [FastChat](/tools/lm-sys-fastchat.md) | [VectorHub](/tools/superlinked-vectorhub.md) | | --- | --- | --- | | Maintenance | Slowing (36%) | Very active (96%) | | Days since push | 98d | 3d | | Open issues (now) | 1.0k | 5 | | Stars delta | Unknown | +5 (30d) | | Open issues delta | Unknown | 0 (30d) | | Full report | [trust report](/tools/lm-sys-fastchat/trust.md) | [trust report](/tools/superlinked-vectorhub/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 ## Decision facts: VectorHub - **Adopt for:** VectorHub hosts Superlinked's deprecated repository for SIE, a self-hosted inference engine designed for embedding generation, OCR, extraction, and document processing tasks. ## Choose when ### Choose FastChat if… - FastChat is primarily Python; VectorHub is Jupyter Notebook. - License: FastChat is Apache-2.0, VectorHub is Other. - 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 VectorHub if… - VectorHub is primarily Jupyter Notebook; FastChat is Python. - License: VectorHub is Other, FastChat is Apache-2.0. - Tags unique to VectorHub: ai, llm, llmops, ml. - Use VectorHub if you require legacy code support for embedding generation, reranking models, or document processing functionalities that are not available in the current version of SIE. ## 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 VectorHub - Avoid VectorHub if you need a more modern and updated inference engine as its repository has been deprecated. - Do not use this tool for production-level work requiring active support or frequent updates, given that it is marked as historical code. ## Common questions ### What is the difference between FastChat and VectorHub? FastChat: An open platform for training, serving, and evaluating large language models. VectorHub: Deprecated repo for developing SIE, an inference engine for embeddings, reranking, OCR, extraction, and document processing. See the comparison table for live GitHub stats and shared categories. ### When should I choose FastChat over VectorHub? Choose FastChat over VectorHub when FastChat is primarily Python; VectorHub is Jupyter Notebook; License: FastChat is Apache-2.0, VectorHub is Other; 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 VectorHub over FastChat? Choose VectorHub over FastChat when VectorHub is primarily Jupyter Notebook; FastChat is Python; License: VectorHub is Other, FastChat is Apache-2.0; Tags unique to VectorHub: ai, llm, llmops, ml; Use VectorHub if you require legacy code support for embedding generation, reranking models, or document processing functionalities that are not available in the current version of SIE. ### 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 VectorHub? Avoid VectorHub if you need a more modern and updated inference engine as its repository has been deprecated. Do not use this tool for production-level work requiring active support or frequent updates, given that it is marked as historical code. ### Is FastChat or VectorHub more popular on GitHub? FastChat has more GitHub stars (39,517 vs 529). Stars measure visibility, not whether either tool fits your constraints. ### Are FastChat and VectorHub open source? Yes - both are open-source projects on GitHub (FastChat: Apache-2.0, VectorHub: Other). ### Where can I find alternatives to FastChat or VectorHub? GraphCanon lists graph-backed alternatives at [FastChat alternatives](/tools/lm-sys-fastchat/alternatives) and [VectorHub alternatives](/tools/superlinked-vectorhub/alternatives) ([FastChat markdown twin](/tools/lm-sys-fastchat/alternatives.md), [VectorHub markdown twin](/tools/superlinked-vectorhub/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-superlinked-vectorhub.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, FastChat or VectorHub? FastChat: Slowing. VectorHub: 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 FastChat and VectorHub? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [FastChat trust report](/tools/lm-sys-fastchat/trust); [VectorHub trust report](/tools/superlinked-vectorhub/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/_