--- title: "FastChat vs llms-tools" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/lm-sys-fastchat-vs-petroivaniuk-llms-tools" tools: ["lm-sys-fastchat", "petroivaniuk-llms-tools"] --- # FastChat vs llms-tools *GraphCanon updated Jul 11, 2026* ## Verdict Pick FastChat when tags unique to FastChat: distributed serving, evaluation system, large-language-models; pick llms-tools when tags unique to llms-tools: ai, chat-bot, chatgpt, data-science. [FastChat](https://github.com/lm-sys/FastChat) reports 39k GitHub stars, 4.8k forks, and 1.0k open issues, last pushed May 1, 2026. [llms-tools](https://github.com/PetroIvaniuk/llms-tools) has 319 stars, 46 forks, and 3 open issues, last pushed Jun 1, 2026. Figures are from public GitHub metadata via [FastChat's repository](https://github.com/lm-sys/FastChat) and [llms-tools's repository](https://github.com/PetroIvaniuk/llms-tools). | | [FastChat](/tools/lm-sys-fastchat.md) | [llms-tools](/tools/petroivaniuk-llms-tools.md) | | --- | --- | --- | | Tagline | An open platform for training, serving, and evaluating large language models | A list of LLMs Tools & Projects | | Stars | 39,490 | 319 | | Forks | 4,788 | 46 | | Open issues | 1,027 | 3 | | Language | 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 | - | | Persona | - | - | | Runtime | - | - | | License | Apache-2.0 | Apache-2.0 | | Categories | Evaluation & Observability, Inference & Serving, LLM Frameworks, Model Training | Evaluation & Observability, LLM Frameworks | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [FastChat](/tools/lm-sys-fastchat.md) | [llms-tools](/tools/petroivaniuk-llms-tools.md) | | --- | --- | --- | | Days since push | 71d | 39d | | Open issues (now) | 1.0k | 3 | | Owner type | Organization | User | | Full report | [trust report](/tools/lm-sys-fastchat/trust.md) | [trust report](/tools/petroivaniuk-llms-tools/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… - Tags unique to FastChat: distributed serving, evaluation system, large-language-models. - Also covers Inference & Serving, Model Training. - - You are looking to train and evaluate state-of-the-art models such as Vicuna or MT-Bench. ### Choose llms-tools if… - Tags unique to llms-tools: ai, chat-bot, chatgpt, data-science. - More recently updated (last pushed Jun 1, 2026). ## 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 llms-tools - Evaluation & Observability: Defer heavyweight eval infra only until you have real traffic - never skip it once users depend on answers. - LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves. ## Common questions ### What is the difference between FastChat and llms-tools? FastChat: An open platform for training, serving, and evaluating large language models. llms-tools: A list of LLMs Tools & Projects. See the comparison table for live GitHub stats and shared categories. ### When should I choose FastChat over llms-tools? Choose FastChat over llms-tools when Tags unique to FastChat: distributed serving, evaluation system, large-language-models; Also covers Inference & Serving, Model Training; - You are looking to train and evaluate state-of-the-art models such as Vicuna or MT-Bench. ### When should I choose llms-tools over FastChat? Choose llms-tools over FastChat when Tags unique to llms-tools: ai, chat-bot, chatgpt, data-science; More recently updated (last pushed Jun 1, 2026). ### 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 llms-tools? Evaluation & Observability: Defer heavyweight eval infra only until you have real traffic - never skip it once users depend on answers. LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves. ### Is FastChat or llms-tools more popular on GitHub? FastChat has more GitHub stars (39,490 vs 319). Stars measure visibility, not whether either tool fits your constraints. ### Are FastChat and llms-tools open source? Yes - both are open-source projects on GitHub (FastChat: Apache-2.0, llms-tools: Apache-2.0). ### Where can I find alternatives to FastChat or llms-tools? GraphCanon lists graph-backed alternatives at [FastChat alternatives](/tools/lm-sys-fastchat/alternatives) and [llms-tools alternatives](/tools/petroivaniuk-llms-tools/alternatives) ([FastChat markdown twin](/tools/lm-sys-fastchat/alternatives.md), [llms-tools markdown twin](/tools/petroivaniuk-llms-tools/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-petroivaniuk-llms-tools.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, FastChat or llms-tools? FastChat: Steady. llms-tools: Steady. 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 llms-tools? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [FastChat trust report](/tools/lm-sys-fastchat/trust); [llms-tools trust report](/tools/petroivaniuk-llms-tools/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/_