---
title: Gacrux-Tiny-1M
canonical_url: "https://www.modelscope.cn/datasets/prithivMLmods/Gacrux-Tiny-1M"
md_url: "https://www.modelscope.cn/datasets/prithivMLmods/Gacrux-Tiny-1M.md"
repository: prithivMLmods/Gacrux-Tiny-1M
last_updated: 2026-03-09
license: apache-2.0
storage_size: "11 GB"
downloads: 119
stars: 0
---

# Gacrux-Tiny-1M

> Gacrux-Tiny-1M - prithivMLmods 在 ModelScope 开源的数据集。Gacrux-Tiny-1M is a compact, high-quality reasoning dataset curated by prithivMLmods, containing 1.06M chain-of-thought reasoning traces optimized for mathematical problem solving, algorithmic coding…

prithivMLmods/Gacrux-Tiny-1M 是 ModelScope 魔搭社区上的数据集，存储大小 11 GB，采用 apache-2.0 许可。

- **Repository**: prithivMLmods/Gacrux-Tiny-1M
- **License**: apache-2.0
- **Storage size**: 11 GB
- **Downloads**: 119
- **Stars**: 0
- **Last updated**: 2026-03-09

Source: https://www.modelscope.cn/datasets/prithivMLmods/Gacrux-Tiny-1M

---

![1](https://cdn-uploads.huggingface.co/production/uploads/65bb837dbfb878f46c77de4c/u4BHIlU7aiN6J6abaSHbJ.png)

# **Gacrux-Tiny-1M**

> **Gacrux-Tiny-1M** is a compact, high-quality reasoning dataset curated by **prithivMLmods**, containing **~1.06M chain-of-thought reasoning traces** optimized for mathematical problem solving, algorithmic coding challenges, and structured reasoning across competitive programming tasks. This dataset is ideal for lightweight reasoning model training and benchmarking. The dataset provides real structured problem statements with detailed reasoning step-by-step solutions that demonstrate problem-solving methods relevant for AI tutoring systems, reasoning LLMs, and code-based reasoning tasks.

## Quick Start

```bash
pip install -U datasets
```

```python
from datasets import load_dataset

dataset = load_dataset("prithivMLmods/Gacrux-Tiny-1M", split="train")
```

## Dataset Overview

| Feature          | Value                                    |
| ---------------- | ---------------------------------------- |
| **Total Rows**   | ~1,066,324                               |
| **Approx. Size** | 12.3 GB                                  |
| **Format**       | Parquet                                  |
| **Language**     | English                                  |
| **License**      | Apache-2.0                               |
| **Domains**      | Math, competitive programming, reasoning |
| **Tags**         | code-x, math, code, agent                |

## Data Structure

* **problem**: Task description from math, programming, and logic domains
* **solution**: Chain-of-thought reasoning and final resolution

## Source Inputs

Includes reasoning from:

* **Xen-Arc AI CodeX-2M-Thinking**: [Small traces, depending on the specific problem] Code-x structured programming logic, [XenArcAI/CodeX-2M-Thinking](https://huggingface.co/datasets/XenArcAI/CodeX-2M-Thinking)
* **Math-aligned custom prompts** : [Gargantua-R1-Compact](https://huggingface.co/datasets/prithivMLmods/Gargantua-R1-Compact)
* **Hybrid algorithmic reasoning tasks**: [Gargantua-R1-Compact](https://huggingface.co/datasets/prithivMLmods/Gargantua-R1-Compact)


## Ideal Use Cases

* Fine-tuning small-to-mid scale reasoning models
* LLM alignment on stepwise chain-of-thought reasoning
* Competitive programming tutoring and explanation agents
* Math problem solver model development
* Code reasoning and debugging training frameworks

## Maintainer

| Author                                                    | Last Updated |
| --------------------------------------------------------- | ------------ |
| **[prithivMLmods](https://huggingface.co/prithivMLmods)** | **Nov 2025** |