--- title: "aikit vs FastChat" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/kaito-project-aikit-vs-lm-sys-fastchat" tools: ["kaito-project-aikit", "lm-sys-fastchat"] --- # aikit vs FastChat *GraphCanon updated Aug 24, 2026* ## Verdict Pick aikit if aikit is a toolkit designed for fine-tuning, building and deploying large language models (LLMs) with an emphasis on open-source technologies; 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. [aikit](https://kaito-project.github.io/aikit/) reports 537 GitHub stars, 57 forks, and 40 open issues, last pushed Aug 24, 2026. [FastChat](https://github.com/lm-sys/FastChat) has 40k stars, 4.8k forks, and 1.0k open issues, last pushed May 1, 2026. Figures are from public GitHub metadata via [aikit's repository](https://github.com/kaito-project/aikit) and [FastChat's repository](https://github.com/lm-sys/FastChat). | | [aikit](/tools/kaito-project-aikit.md) | [FastChat](/tools/lm-sys-fastchat.md) | | --- | --- | --- | | Tagline | Fine-tune, build, and deploy open-source LLMs easily! | An open platform for training, serving, and evaluating large language models | | Stars | 537 | 39,517 | | Forks | 57 | 4,788 | | Open issues | 40 | 1,038 | | Language | Go | Python | | Adopt for | Aikit is a toolkit designed for fine-tuning, building and deploying large language models (LLMs) with an emphasis on open-source technologies. | 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 | MIT | Apache-2.0 | | Categories | Inference & Serving, LLM Frameworks, Model Training | Evaluation & Observability, Inference & Serving, LLM Frameworks, Model Training | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [aikit](/tools/kaito-project-aikit.md) | [FastChat](/tools/lm-sys-fastchat.md) | | --- | --- | --- | | Maintenance | Very active (96%) | Slowing (36%) | | Days since push | 0d | 98d | | Open issues (now) | 40 | 1.0k | | Stars delta | +3 (30d) | Unknown | | Open issues delta | -3 (30d) | Unknown | | Full report | [trust report](/tools/kaito-project-aikit/trust.md) | [trust report](/tools/lm-sys-fastchat/trust.md) | ## Decision facts: aikit - **Adopt for:** Aikit is a toolkit designed for fine-tuning, building and deploying large language models (LLMs) with an emphasis on open-source technologies. ## 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 aikit if… - aikit is primarily Go; FastChat is Python. - License: aikit is MIT, FastChat is Apache-2.0. - Tags unique to aikit: ai, buildkit, chatgpt, docker. - aikit ships Docker support for self-hosted deployment. - - You need a flexible solution specifically built using Go and prefer its concurrency model. ### Choose FastChat if… - FastChat is primarily Python; aikit is Go. - License: FastChat is Apache-2.0, aikit is MIT. - Tags unique to FastChat: chatbots, distributed-serving, evaluation system, large language models. - Also covers Evaluation & Observability. - - You are looking to train and evaluate state-of-the-art models such as Vicuna or MT-Bench. ## When NOT to use aikit - - You have a preference or requirement for Python-based tools due to the lack of native support in Aikit. - - If your deployment setup strictly uses cloud-specific platforms and you do not use Kubernetes or Docker, as Aikit heavily integrates with containerized environments like these. ## 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. ## Common questions ### What is the difference between aikit and FastChat? aikit: Fine-tune, build, and deploy open-source LLMs easily!. FastChat: An open platform for training, serving, and evaluating large language models. See the comparison table for live GitHub stats and shared categories. ### When should I choose aikit over FastChat? Choose aikit over FastChat when aikit is primarily Go; FastChat is Python; License: aikit is MIT, FastChat is Apache-2.0; Tags unique to aikit: ai, buildkit, chatgpt, docker; aikit ships Docker support for self-hosted deployment; - You need a flexible solution specifically built using Go and prefer its concurrency model. ### When should I choose FastChat over aikit? Choose FastChat over aikit when FastChat is primarily Python; aikit is Go; License: FastChat is Apache-2.0, aikit is MIT; Tags unique to FastChat: chatbots, distributed-serving, evaluation system, large language models; Also covers Evaluation & Observability; - You are looking to train and evaluate state-of-the-art models such as Vicuna or MT-Bench. ### When should I avoid aikit? - You have a preference or requirement for Python-based tools due to the lack of native support in Aikit. - If your deployment setup strictly uses cloud-specific platforms and you do not use Kubernetes or Docker, as Aikit heavily integrates with containerized environments like these. ### 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. ### Is aikit or FastChat more popular on GitHub? FastChat has more GitHub stars (39,517 vs 537). Stars measure visibility, not whether either tool fits your constraints. ### Are aikit and FastChat open source? Yes - both are open-source projects on GitHub (aikit: MIT, FastChat: Apache-2.0). ### Where can I find alternatives to aikit or FastChat? GraphCanon lists graph-backed alternatives at [aikit alternatives](/tools/kaito-project-aikit/alternatives) and [FastChat alternatives](/tools/lm-sys-fastchat/alternatives) ([aikit markdown twin](/tools/kaito-project-aikit/alternatives.md), [FastChat markdown twin](/tools/lm-sys-fastchat/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/kaito-project-aikit-vs-lm-sys-fastchat.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, aikit or FastChat? aikit: Very active. FastChat: 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 aikit and FastChat? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [aikit trust report](/tools/kaito-project-aikit/trust); [FastChat trust report](/tools/lm-sys-fastchat/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=kaito-project-aikit`](/api/graphcanon/graph?tool=kaito-project-aikit) - 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/_