--- title: "FastChat vs HRM" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/lm-sys-fastchat-vs-sapientinc-hrm" tools: ["lm-sys-fastchat", "sapientinc-hrm"] --- # FastChat vs HRM *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 HRM if hierarchical Reasoning Model (HRM) is a brain-inspired AI tool centered on deep learning and hierarchical reasoning. It necessitates CUDA 12.6 for its. [FastChat](https://github.com/lm-sys/FastChat) reports 40k GitHub stars, 4.8k forks, and 1.0k open issues, last pushed May 1, 2026. [HRM](https://sapient.inc) has 13k stars, 1.8k forks, and 75 open issues, last pushed Mar 31, 2026. Figures are from public GitHub metadata via [FastChat's repository](https://github.com/lm-sys/FastChat) and [HRM's repository](https://github.com/sapientinc/HRM). | | [FastChat](/tools/lm-sys-fastchat.md) | [HRM](/tools/sapientinc-hrm.md) | | --- | --- | --- | | Tagline | An open platform for training, serving, and evaluating large language models | Hierarchical Reasoning Model Official Release | | Stars | 39,517 | 12,613 | | Forks | 4,788 | 1,825 | | Open issues | 1,038 | 75 | | 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 | Hierarchical Reasoning Model (HRM) is a brain-inspired AI tool centered on deep learning and hierarchical reasoning. It necessitates CUDA 12.6 for its PyTorch-based environment setup, making it uniquely optimized for GPU | | Persona | - | - | | Runtime | - | - | | License | Apache-2.0 | Apache-2.0 | | Categories | Evaluation & Observability, Inference & Serving, LLM Frameworks, Model Training | LLM Frameworks, Model Training | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [FastChat](/tools/lm-sys-fastchat.md) | [HRM](/tools/sapientinc-hrm.md) | | --- | --- | --- | | Days since push | 98d | 138d | | Open issues (now) | 1.0k | 75 | | Stars delta | Unknown | +17 (30d) | | Open issues delta | Unknown | 0 (30d) | | Full report | [trust report](/tools/lm-sys-fastchat/trust.md) | [trust report](/tools/sapientinc-hrm/trust.md) | ## Shared compatibility - **Python**: [FastChat](/tools/lm-sys-fastchat.md) - Python runtime; [HRM](/tools/sapientinc-hrm.md) - Python runtime ## 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: HRM - **Adopt for:** Hierarchical Reasoning Model (HRM) is a brain-inspired AI tool centered on deep learning and hierarchical reasoning. It necessitates CUDA 12.6 for its PyTorch-based environment setup, making it uniquely optimized for GPU ## Choose when ### Choose FastChat if… - Tags unique to FastChat: chatbots, distributed-serving, evaluation system. - Also covers Evaluation & Observability, Inference & Serving. - - You are looking to train and evaluate state-of-the-art models such as Vicuna or MT-Bench. ### Choose HRM if… - Tags unique to HRM: brain-inspired-ai, deep-learning, reasoning. - Consider HRM when you need to leverage a highly specific GPU version (CUDA 12.6) which can potentially offer the latest in computational capabilities tailored for deep learning tasks. - Leaner open-issue backlog (75). ## 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 HRM - Avoid using HRM if you face limitations or challenges in accessing CUDA 12.6 specifically, as the model is tightly coupled with this version of CUDA and other versions will not be compatible. - Do not use HRM if your project does not benefit from hierarchical reasoning models; its specialized architecture could represent an unnecessary complexity. ## Common questions ### What is the difference between FastChat and HRM? FastChat: An open platform for training, serving, and evaluating large language models. HRM: Hierarchical Reasoning Model Official Release. See the comparison table for live GitHub stats and shared categories. ### When should I choose FastChat over HRM? Choose FastChat over HRM when Tags unique to FastChat: chatbots, distributed-serving, evaluation system; Also covers Evaluation & Observability, Inference & Serving; - You are looking to train and evaluate state-of-the-art models such as Vicuna or MT-Bench. ### When should I choose HRM over FastChat? Choose HRM over FastChat when Tags unique to HRM: brain-inspired-ai, deep-learning, reasoning; Consider HRM when you need to leverage a highly specific GPU version (CUDA 12.6) which can potentially offer the latest in computational capabilities tailored for deep learning tasks; Leaner open-issue backlog (75). ### 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 HRM? Avoid using HRM if you face limitations or challenges in accessing CUDA 12.6 specifically, as the model is tightly coupled with this version of CUDA and other versions will not be compatible. Do not use HRM if your project does not benefit from hierarchical reasoning models; its specialized architecture could represent an unnecessary complexity. ### Is FastChat or HRM more popular on GitHub? FastChat has more GitHub stars (39,517 vs 12,613). Stars measure visibility, not whether either tool fits your constraints. ### Are FastChat and HRM open source? Yes - both are open-source projects on GitHub (FastChat: Apache-2.0, HRM: Apache-2.0). ### Where can I find alternatives to FastChat or HRM? GraphCanon lists graph-backed alternatives at [FastChat alternatives](/tools/lm-sys-fastchat/alternatives) and [HRM alternatives](/tools/sapientinc-hrm/alternatives) ([FastChat markdown twin](/tools/lm-sys-fastchat/alternatives.md), [HRM markdown twin](/tools/sapientinc-hrm/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-sapientinc-hrm.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, FastChat or HRM? FastChat: Slowing. HRM: 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 FastChat and HRM? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [FastChat trust report](/tools/lm-sys-fastchat/trust); [HRM trust report](/tools/sapientinc-hrm/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/_