Comparison
FastChat vs HRM
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.
Markdown twin · FastChat alternatives · HRM alternatives
GraphCanon updated 3d
Trust & integrity
| Signal | FastChat | HRM |
|---|---|---|
| Maintenance | Slowing (98d since push) As of 1w · github_public_v1 | Slowing (138d since push) As of 3d · github_public_v1 |
| Provenance | Not a fork · Organization account As of 1w · github_public_v1 | Not a fork · Organization account As of 3d · github_public_v1 |
| OSV dependency advisories | No lockfile (source not queried) As of 1mo · osv@v1 | No published findings from this source as of 2026-07-11 As of 1mo · osv@v1 |
| deps.dev advisories | Not queried deps.dev@v1 | Not queried deps.dev@v1 |
| OpenSSF Scorecard | Not queried openssf-scorecard@v1 | Not queried openssf-scorecard@v1 |
Tagline
- FastChat
- An open platform for training, serving, and evaluating large language models
- HRM
- Hierarchical Reasoning Model Official Release
Stars
- FastChat
- 40k
- HRM
- 13k
Forks
- FastChat
- 4.8k
- HRM
- 1.8k
Open issues
- FastChat
- 1.0k
- HRM
- 75
Language
- FastChat
- Python
- HRM
- Python
Adopt for
- FastChat
- 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
- HRM
- 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
- FastChat
- -
- HRM
- -
Runtime
- FastChat
- -
- HRM
- -
License
- FastChat
- Apache-2.0
- HRM
- Apache-2.0
Last pushed
- FastChat
- May 1, 2026
- HRM
- Mar 31, 2026
Categories
- FastChat
- Evaluation & Observability, Inference & Serving, LLM Frameworks, Model Training
- HRM
- LLM Frameworks, Model Training
Trust and health
Days since push
- FastChat
- 98d
- HRM
- 138d
Open issues (now)
- FastChat
- 1.0k
- HRM
- 75
Stars delta
- FastChat
- Unknown
- HRM
- +17 (30d)
Open issues delta
- FastChat
- Unknown
- HRM
- 0 (30d)
OSV dependency advisories
- FastChat
- No lockfile (source not queried)
- HRM
- No published findings from this source as of 2026-07-11
Full report
- FastChat
- Trust report
- HRM
- Trust report
Shared compatibility
- Python · FastChat: Python runtime · HRM: Python runtime
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.
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.
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 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.
Explore
Sources
Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.
- GitHub stars (lm-sys/FastChat) · observed Aug 7, 2026
- GitHub forks (lm-sys/FastChat) · observed Aug 7, 2026
- Last push (lm-sys/FastChat) · observed May 1, 2026
- License file (Apache-2.0) · observed Aug 7, 2026
- Decision facts (enrichment) · observed Jul 11, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
- GitHub stars (sapientinc/HRM) · observed Aug 17, 2026
- GitHub forks (sapientinc/HRM) · observed Aug 17, 2026
- Last push (sapientinc/HRM) · observed Mar 31, 2026
- License file (Apache-2.0) · observed Aug 17, 2026
- Decision facts (enrichment) · observed Jul 11, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
GitHub stars on cards: FastChat 40k · HRM 13k (synced Aug 7, 2026).
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 and HRM alternatives (FastChat markdown twin, HRM markdown twin), 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 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; HRM trust report.