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HRM

Hierarchical Reasoning Model Official Release

GraphCanon updated 4d · GitHub synced 4d

13k stars1.8k forksLast push 4mo Python Apache-2.0

Decision brief

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

Good fit when

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.
If your project demands brain-inspired hierarchical reasoning features that align closely with human cognitive processes, this tool could provide unique advantages over others that do not incorporate脑

Avoid when

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.

Observed Jul 11, 2026 · Source: enrich:decision_facts

HRM alternatives Trust report

HRM vs langextract

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Maintenance and security

Full trust report

Maintenance: Slowing (138d since push); As of 4d
Provenance: Not a fork · Organization account; As of 4d
Security (OSV): No criticals; As of 1mo

Public GitHub metadata and optional OSV scans. Signals, not a guarantee. Trust methodology.

Install

pip install HRM

How it fits your stack(8)

Typed graph edges - alternatives, integrations, successors, and dependencies. Ranked by relationship type, not raw GitHub stars.

Alternative

HRM is a hierarchical reasoning model for efficient sequential reasoning with limited data. Langextract is a Python library that uses large language models to extract structured info from unstructured text. Both tools handle textual information extraction and analysis but use different methods; HRM relies on neural networks.

Integrates

HRM integrates with transformers by leveraging the latter's extensive collection of pre-trained models and its framework for serving machine learning tasks, thereby extending HRM's capabilities in processing sequential data through the integration of state-of-the-art transformer-based architectures from the transformers library.

Related

Tool for building and deploying AI-powered agents and workflows

LLMs-from-scratch

HRM shares similarities with LLMs-from-scratch in terms of deep-learning and large-language-models, as both projects aim to develop models from scratch.

HRM can possibly be applied or integrated into the multi-agent AI applications created with autogen given their focus on complex, intelligent systems and hierarchical reasoning.

Relationship graph

Optional deeper exploration of typed edges and category neighbours.

langextract38k★

transformers164k★

tensorflow197k★

langflow153k★

LLMs-from-scratch103k★

AlternativeIntegratesRelated

langextract38k★

transformers164k★

tensorflow197k★

langflow153k★

LLMs-from-scratch103k★

AlternativeIntegratesRelated

Similar tools

Same-category neighbours not already linked as typed edges.

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Evidence and technical details

Sourced facts, taxonomy, compatibility claims, README excerpt, and machine-readable endpoints.

Overview

A brain-inspired AI model focused on deep learning and reasoning through hierarchical structures. Requires CUDA 12.6 for PyTorch installation.

Capability facts

Languages: python
Source: github.language · Aug 17, 2026

Categories

LLM Frameworks Model Training

Compatibility

Sourced claims from the README excerpt - not unsourced marketing copy.

Python runtimePython

Source: README excerpt (regex_v1, Aug 17, 2026)

## Install Python Dependencies 🐍

Tags

brain-inspired-ai deep-learning large language models reasoning

README

Install CUDA 12.6

CUDA_URL=https://developer.download.nvidia.com/compute/cuda/12.6.3/local_installers/cuda_12.6.3_560.35.05_linux.run

wget -q --show-progress --progress=bar:force:noscroll -O cuda_installer.run $CUDA_URL sudo sh cuda_installer.run --silent --toolkit --override

export CUDA_HOME=/usr/local/cuda-12.6

Install PyTorch with CUDA 12.6

PYTORCH_INDEX_URL=https://download.pytorch.org/whl/cu126

pip3 install torch torchvision torchaudio --index-url $PYTORCH_INDEX_URL

Install Python Dependencies 🐍

pip install -r requirements.txt

For agents

This page has a .md twin and JSON over the API.

/tools/sapientinc-hrm.md GET /api/graphcanon/tools/sapientinc-hrm GET /api/graphcanon/graph?tool=sapientinc-hrm

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