--- title: "FastChat vs TNN" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/lm-sys-fastchat-vs-tencent-tnn" tools: ["lm-sys-fastchat", "tencent-tnn"] --- # FastChat vs TNN *GraphCanon updated Jul 11, 2026* ## Verdict Pick FastChat when fastChat is primarily Python; TNN is C++; pick TNN when tNN is primarily C++; FastChat is Python. [FastChat](https://github.com/lm-sys/FastChat) reports 39k GitHub stars, 4.8k forks, and 1.0k open issues, last pushed May 1, 2026. [TNN](https://github.com/Tencent/TNN) has 4.6k stars, 773 forks, and 318 open issues, last pushed May 9, 2025. Figures are from public GitHub metadata via [FastChat's repository](https://github.com/lm-sys/FastChat) and [TNN's repository](https://github.com/Tencent/TNN). | | [FastChat](/tools/lm-sys-fastchat.md) | [TNN](/tools/tencent-tnn.md) | | --- | --- | --- | | Tagline | An open platform for training, serving, and evaluating large language models | TNN: developed by Tencent Youtu Lab and Guangying Lab, a uniform deep learning inference framework for mobile、desktop and server. TNN is distinguished by several outstanding features, including its cr | | Stars | 39,490 | 4,640 | | Forks | 4,788 | 773 | | Open issues | 1,027 | 318 | | Language | Python | C++ | | 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 | Other | | Categories | Model Training, LLM Frameworks, Inference & Serving, Evaluation & Observability | Model Training, Computer Vision, Inference & Serving | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [FastChat](/tools/lm-sys-fastchat.md) | [TNN](/tools/tencent-tnn.md) | | --- | --- | --- | | Maintenance | Steady (60%) | Dormant (18%) | | Days since push | 71d | 428d | | Open issues (now) | 1.0k | 318 | | Full report | [trust report](/tools/lm-sys-fastchat/trust.md) | [trust report](/tools/tencent-tnn/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… - FastChat is primarily Python; TNN is C++. - License: FastChat is Apache-2.0, TNN is Other. - Tags unique to FastChat: evaluation system, large-language-models, chatbots, distributed serving. - Also covers LLM Frameworks, Evaluation & Observability. - - You are looking to train and evaluate state-of-the-art models such as Vicuna or MT-Bench. ### Choose TNN if… - TNN is primarily C++; FastChat is Python. - License: TNN is Other, FastChat is Apache-2.0. - Tags unique to TNN: deep-learning, ncnn, face-detection, mnn. - Also covers Computer Vision. - TNN ships Docker support for self-hosted deployment. ## 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 TNN - Last GitHub push was 429 days ago (dormant maintenance, May 9, 2025). Validate activity before betting a new project on TNN. - Model Training: Try prompting and RAG first; fine-tuning is the answer to style/format, not missing knowledge. - Inference & Serving: Self-hosting rarely beats a hosted API on cost until you have steady, high-volume traffic. ## Common questions ### What is the difference between FastChat and TNN? FastChat: An open platform for training, serving, and evaluating large language models. TNN: TNN: developed by Tencent Youtu Lab and Guangying Lab, a uniform deep learning inference framework for mobile、desktop and server. TNN is distinguished by several outstanding features, including its cr. See the comparison table for live GitHub stats and shared categories. ### When should I choose FastChat over TNN? Choose FastChat over TNN when FastChat is primarily Python; TNN is C++; License: FastChat is Apache-2.0, TNN is Other; Tags unique to FastChat: evaluation system, large-language-models, chatbots, distributed serving; Also covers LLM Frameworks, Evaluation & Observability; - You are looking to train and evaluate state-of-the-art models such as Vicuna or MT-Bench. ### When should I choose TNN over FastChat? Choose TNN over FastChat when TNN is primarily C++; FastChat is Python; License: TNN is Other, FastChat is Apache-2.0; Tags unique to TNN: deep-learning, ncnn, face-detection, mnn; Also covers Computer Vision; TNN ships Docker support for self-hosted deployment. ### 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 TNN? Last GitHub push was 429 days ago (dormant maintenance, May 9, 2025). Validate activity before betting a new project on TNN. Model Training: Try prompting and RAG first; fine-tuning is the answer to style/format, not missing knowledge. Inference & Serving: Self-hosting rarely beats a hosted API on cost until you have steady, high-volume traffic. ### Is FastChat or TNN more popular on GitHub? FastChat has more GitHub stars (39,490 vs 4,640). Stars measure visibility, not whether either tool fits your constraints. ### Are FastChat and TNN open source? Yes - both are open-source projects on GitHub (FastChat: Apache-2.0, TNN: Other). ### Where can I find alternatives to FastChat or TNN? GraphCanon lists graph-backed alternatives at [FastChat alternatives](/tools/lm-sys-fastchat/alternatives) and [TNN alternatives](/tools/tencent-tnn/alternatives) ([FastChat markdown twin](/tools/lm-sys-fastchat/alternatives.md), [TNN markdown twin](/tools/tencent-tnn/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-tencent-tnn.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, FastChat or TNN? FastChat: Steady. TNN: 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 TNN? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [FastChat trust report](/tools/lm-sys-fastchat/trust); [TNN trust report](/tools/tencent-tnn/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/_