--- title: "FastChat vs optimate" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/lm-sys-fastchat-vs-nebuly-ai-optimate" tools: ["lm-sys-fastchat", "nebuly-ai-optimate"] --- # FastChat vs optimate *GraphCanon updated Aug 17, 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 optimate if optiMate is a collection of open-source libraries in Python designed to optimize the performance and resource utilization of AI models, though it. [FastChat](https://github.com/lm-sys/FastChat) reports 40k GitHub stars, 4.8k forks, and 1.0k open issues, last pushed May 1, 2026. [optimate](https://www.nebuly.com/) has 8.3k stars, 617 forks, and 110 open issues, last pushed Jul 22, 2024. Figures are from public GitHub metadata via [FastChat's repository](https://github.com/lm-sys/FastChat) and [optimate's repository](https://github.com/nebuly-ai/optimate). | | [FastChat](/tools/lm-sys-fastchat.md) | [optimate](/tools/nebuly-ai-optimate.md) | | --- | --- | --- | | Tagline | An open platform for training, serving, and evaluating large language models | A collection of libraries to optimize AI model performances | | Stars | 39,517 | 8,329 | | Forks | 4,788 | 617 | | Open issues | 1,038 | 110 | | 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 | OptiMate is a collection of open-source libraries in Python designed to optimize the performance and resource utilization of AI models, though it now operates in a legacy phase meaning no further updates or official code | | Persona | - | - | | Runtime | - | - | | License | Apache-2.0 | Apache-2.0 | | 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) | [optimate](/tools/nebuly-ai-optimate.md) | | --- | --- | --- | | Maintenance | Slowing (36%) | Dormant (18%) | | Days since push | 98d | 756d | | Open issues (now) | 1.0k | 110 | | Stars delta | Unknown | -3 (30d) | | Open issues delta | Unknown | 0 (30d) | | Full report | [trust report](/tools/lm-sys-fastchat/trust.md) | [trust report](/tools/nebuly-ai-optimate/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: optimate - **Adopt for:** OptiMate is a collection of open-source libraries in Python designed to optimize the performance and resource utilization of AI models, though it now operates in a legacy phase meaning no further updates or official code ## Choose when ### Choose FastChat if… - Tags unique to FastChat: chatbots, distributed-serving, evaluation system. - 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 optimate if… - Tags unique to optimate: ai, analytics, artificial-intelligence, deeplearning. - When you need optimization techniques for enhancing inference costs by leveraging state-of-the-art approaches that couple your AI models with hardware like GPUs and CPUs through tools such as Speedスター - Leaner open-issue backlog (110). ## 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 optimate - Do not use OptiMate if you need ongoing support or active development. The project has moved into a legacy phase and receives no further updates - Avoid using OptiMate for future AI deployment if you are aiming to integrate state-of-the-art real-time observability features as it's no longer actively maintained nor receiving new improvements ## Common questions ### What is the difference between FastChat and optimate? FastChat: An open platform for training, serving, and evaluating large language models. optimate: A collection of libraries to optimize AI model performances. See the comparison table for live GitHub stats and shared categories. ### When should I choose FastChat over optimate? Choose FastChat over optimate when Tags unique to FastChat: chatbots, distributed-serving, evaluation system; 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 optimate over FastChat? Choose optimate over FastChat when Tags unique to optimate: ai, analytics, artificial-intelligence, deeplearning; When you need optimization techniques for enhancing inference costs by leveraging state-of-the-art approaches that couple your AI models with hardware like GPUs and CPUs through tools such as Speedスター; Leaner open-issue backlog (110). ### 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 optimate? Do not use OptiMate if you need ongoing support or active development. The project has moved into a legacy phase and receives no further updates Avoid using OptiMate for future AI deployment if you are aiming to integrate state-of-the-art real-time observability features as it's no longer actively maintained nor receiving new improvements ### Is FastChat or optimate more popular on GitHub? FastChat has more GitHub stars (39,517 vs 8,329). Stars measure visibility, not whether either tool fits your constraints. ### Are FastChat and optimate open source? Yes - both are open-source projects on GitHub (FastChat: Apache-2.0, optimate: Apache-2.0). ### Where can I find alternatives to FastChat or optimate? GraphCanon lists graph-backed alternatives at [FastChat alternatives](/tools/lm-sys-fastchat/alternatives) and [optimate alternatives](/tools/nebuly-ai-optimate/alternatives) ([FastChat markdown twin](/tools/lm-sys-fastchat/alternatives.md), [optimate markdown twin](/tools/nebuly-ai-optimate/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-nebuly-ai-optimate.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, FastChat or optimate? FastChat: Slowing. optimate: 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 optimate? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [FastChat trust report](/tools/lm-sys-fastchat/trust); [optimate trust report](/tools/nebuly-ai-optimate/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/_