Beginner score
30/100
Competition workspace
适合想基于文心4.5开源模型做完整作品的开发者，可选择多模态应用赛道或AI硬件赛道。多模态赛道需要能处理图像、视频、文档、OCR或语音等模态并构建交互式应用；硬件赛道还需要软硬件整合与在树莓派、Jetson Nano等设备端部署模型的能力。
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…
适合想基于文心4.5开源模型做完整作品的开发者，可选择多模态应用赛道或AI硬件赛道。多模态赛道需要能处理图像、视频、文档、OCR或语音等模态并构建交互式应用；硬件赛道还需要软硬件整合与在树莓派、Jetson Nano等设备端部署模型的能力。
If the items below still feel unfamiliar, you usually get a better result by preparing first instead of rushing in.
文心4.5开源模型开发
多模态应用构建
模型微调与量化
RAG与知识库构建
端侧模型部署
Git与开源项目文档编写
The real friction is usually not library usage. It is validation, time allocation, and task framing.
难点不只是调用模型，而是交付可复现、可运行的完整开源项目：需要说明模型优化和效果对比，并提供部署、训练与推理代码。硬件赛道尤其要求在设备端实现完整AI功能，同时权衡性能、功耗与成本。
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.
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Rules, files, submission details, and the live deadline still come from the official page.
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LLMSeparate 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.