--- title: "FastChat vs oumi" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/lm-sys-fastchat-vs-oumi-ai-oumi" tools: ["lm-sys-fastchat", "oumi-ai-oumi"] --- # FastChat vs oumi *GraphCanon updated Aug 23, 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 oumi if oumi is a tool for fine-tuning, evaluating, and deploying open-source large language models (LLMs) such as Gemma 4, Qwen3.5, Qwen3.6, gpt-oss, DeepSeek-R1. [FastChat](https://github.com/lm-sys/FastChat) reports 40k GitHub stars, 4.8k forks, and 1.0k open issues, last pushed May 1, 2026. [oumi](https://oumi.ai) has 9.4k stars, 784 forks, and 34 open issues, last pushed Aug 21, 2026. Figures are from public GitHub metadata via [FastChat's repository](https://github.com/lm-sys/FastChat) and [oumi's repository](https://github.com/oumi-ai/oumi). | | [FastChat](/tools/lm-sys-fastchat.md) | [oumi](/tools/oumi-ai-oumi.md) | | --- | --- | --- | | Tagline | An open platform for training, serving, and evaluating large language models | Easily fine-tune, evaluate and deploy open source LLMs/VLMs | | Stars | 39,517 | 9,376 | | Forks | 4,788 | 784 | | Open issues | 1,038 | 34 | | 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 | Oumi is a tool for fine-tuning, evaluating, and deploying open-source large language models (LLMs) such as Gemma 4, Qwen3.5, Qwen3.6, gpt-oss, DeepSeek-R1, among others. | | Persona | - | - | | Runtime | - | - | | License | Apache-2.0 | Oumi is released under Apache-2.0 license, providing users with a permissive free software license that includes the terms of the MIT License while also addressing patent liability issues. | | Categories | Evaluation & Observability, Inference & Serving, LLM Frameworks, Model Training | Evaluation & Observability, Inference & Serving, Model Training | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [FastChat](/tools/lm-sys-fastchat.md) | [oumi](/tools/oumi-ai-oumi.md) | | --- | --- | --- | | Maintenance | Slowing (36%) | Very active (96%) | | Days since push | 98d | 1d | | Open issues (now) | 1.0k | 34 | | Stars delta | Unknown | +17 (30d) | | Open issues delta | Unknown | +3 (30d) | | Full report | [trust report](/tools/lm-sys-fastchat/trust.md) | [trust report](/tools/oumi-ai-oumi/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: oumi - **Requirements:** Requires Docker; Docker is used for standardized and portable environment deployments. - **Adopt for:** Oumi is a tool for fine-tuning, evaluating, and deploying open-source large language models (LLMs) such as Gemma 4, Qwen3.5, Qwen3.6, gpt-oss, DeepSeek-R1, among others. - **License detail:** Oumi is released under Apache-2.0 license, providing users with a permissive free software license that includes the terms of the MIT License while also addressing patent liability issues. ## Choose when ### Choose FastChat if… - Tags unique to FastChat: chatbots, distributed-serving, evaluation system, large language models. - Also covers LLM Frameworks. - - You are looking to train and evaluate state-of-the-art models such as Vicuna or MT-Bench. ### Choose oumi if… - Requirements: Requires Docker; Docker is used for standardized and portable environment deployments.. - Tags unique to oumi: dpo, evaluation, fine-tuning, llms. - oumi ships Docker support for self-hosted deployment. - - You are working specifically with one of the supported open-source LLMs including Gemma 4 or Qwen variants. ## 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 oumi - - If your focus is on proprietary models rather than open-source ones, Oumi may not offer the necessary support or integrations. - - You require deployment flexibility beyond what Oumi provides for less commonly supported open-source LLMs outside its primary focus (e.g., Gemma 4, Qwen series). ## Common questions ### What is the difference between FastChat and oumi? FastChat: An open platform for training, serving, and evaluating large language models. oumi: Easily fine-tune, evaluate and deploy open source LLMs/VLMs. See the comparison table for live GitHub stats and shared categories. ### When should I choose FastChat over oumi? Choose FastChat over oumi when Tags unique to FastChat: chatbots, distributed-serving, evaluation system, large language models; Also covers LLM Frameworks; - You are looking to train and evaluate state-of-the-art models such as Vicuna or MT-Bench. ### When should I choose oumi over FastChat? Choose oumi over FastChat when Requirements: Requires Docker; Docker is used for standardized and portable environment deployments.; Tags unique to oumi: dpo, evaluation, fine-tuning, llms; oumi ships Docker support for self-hosted deployment; - You are working specifically with one of the supported open-source LLMs including Gemma 4 or Qwen variants. ### 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 oumi? - If your focus is on proprietary models rather than open-source ones, Oumi may not offer the necessary support or integrations. - You require deployment flexibility beyond what Oumi provides for less commonly supported open-source LLMs outside its primary focus (e.g., Gemma 4, Qwen series). ### Is FastChat or oumi more popular on GitHub? FastChat has more GitHub stars (39,517 vs 9,376). Stars measure visibility, not whether either tool fits your constraints. ### Are FastChat and oumi open source? Yes - both are open-source projects on GitHub (FastChat: Apache-2.0, oumi: Apache-2.0). ### Where can I find alternatives to FastChat or oumi? GraphCanon lists graph-backed alternatives at [FastChat alternatives](/tools/lm-sys-fastchat/alternatives) and [oumi alternatives](/tools/oumi-ai-oumi/alternatives) ([FastChat markdown twin](/tools/lm-sys-fastchat/alternatives.md), [oumi markdown twin](/tools/oumi-ai-oumi/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-oumi-ai-oumi.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, FastChat or oumi? FastChat: Slowing. oumi: 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 oumi? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [FastChat trust report](/tools/lm-sys-fastchat/trust); [oumi trust report](/tools/oumi-ai-oumi/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/_