Beginner score
30/100
Competition workspace
适合已有可开源AI项目、能够组队完成产品化交付的科研AI开发者、机器人/硬件工程师和Agent应用开发者。科研赛道需要能在真实科研场景验证模型、工具或框架；具身赛道需要实际硬件平台或明确硬件规范；Agent赛道需要处理社区问答数据、模型微调与API或Web部署。
Suggested next step
Decide whether this contest fits your current stage before you sink time into the leaderboard.
Beginner score
30/100
Learning value
60/100
Estimated effort
24-80 hours
Metric
Official scoring is published on the Op…
适合已有可开源AI项目、能够组队完成产品化交付的科研AI开发者、机器人/硬件工程师和Agent应用开发者。科研赛道需要能在真实科研场景验证模型、工具或框架；具身赛道需要实际硬件平台或明确硬件规范；Agent赛道需要处理社区问答数据、模型微调与API或Web部署。
If the items below still feel unfamiliar, you usually get a better result by preparing first instead of rushing in.
开源项目文档编写
实验复现与评测
Python与AI模型开发
模型部署
技术演示视频制作
路演答辩
The real friction is usually not library usage. It is validation, time allocation, and task framing.
难点不只是做出模型，而是交付可审查、可复现、可开源的完整项目：代码、文档、示例、实验或测试报告，以及对应赛道的真实应用验证、硬件/仿真演示或可部署答疑系统。入围后还需参加线下路演，作品完整性和展示效果会直接增加准备工作。
This guide is the best pre-read if you want a cleaner start instead of trial-and-error.
How to learn feature engineering, validation, and competition workflow without heavy hardware.
No GPU? Pick Competitions That Still Teach You Good HabitsUse these fields to make a quick decision before you dive deeper.
Registration is unverified; confirm availability on the official page before investing.
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Rules, files, submission details, and the live deadline still come from the official page.
These competitions share a similar domain or difficulty level.
ModelScope
General MLModelScope
General MLKaggle
General MLKaggle
General MLSeparate what is confirmed from what still needs review. Official rules and deadlines win — report anything that looks wrong.
Official metric is not published on the OpenAtom competition listing; verify scoring on the competition page.
reward_value_usd is a rough CNY→USD estimate (×0.14) for ranking only; use reward_summary for the official prize text.