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  3. FDE实战松·前线交付战
ModelScopeLLMIntermediateRegistration closed

FDE实战松·前线交付战

A intermediate llm competition requiring roughly 10–30 hours for an end-to-end practice run.

Difficulty
Intermediate
Estimated effort
10–30 hours
Registration deadline
Sep 17, 2026
Compute
Free GPU OK
OverviewPreparationSource

Overview

Who this competition fits

适合想做面向客户的 AI/Agent 方案交付的人:需要能把技术实现、产品方案和商业判断结合起来,并在现场完成 Demo、演示材料与报价。可 1—3 人组队参加。

Read the original official blurb
FDE实战松前线交付战由云谷中心、魔搭社区与蜂元智能主办,2026年9月21日在云谷中心单日线下举行,设具身智能数据工厂、园区运营AI提效两条赛道,二十支队伍,每队一到三人。本场所有赛题的甲方均由甲方Agent扮演,开发时段不设真人答疑,各队信息条件与问询额度完全相同,差距只来自你问出了什么,以及怎么把答复落进方案。当天须交出方案文档、商业报价单和可运行的魔搭创空间Demo,评审围绕客户价值、需求洞察、产品形态、实施可行性与商业报价打分。 Official category: hackathon. Participants: 0. Organizers: 魔搭社区, 云谷中心, 蜂元智能.

Preparation

From registration to a first submission

  1. 01

    Agent 应用设计

  2. 02

    需求访谈与需求挖掘

  3. 03

    Demo 开发

  4. 04

    方案撰写

  5. 05

    演示材料制作

  6. 06

    商业报价设计

Before you commit: 难点不只是做出技术 Demo,而是要通过 Agent 模拟甲方沟通,主动挖掘需求、预算、文档和业务限制,再把这些信息转成甲方可能愿意购买的完整交付方案与商业报价。

Source

How this page was assembled

Competition information is structured from the official page. Scores are platform estimates for decision support; official rules take precedence.

Official competition page
ModelScope
Registration
Open signup form
Last checked
Sep 14, 2026

Entry assessment

est.
55

Prepare before joining

Overall fit estimate

Beginner fit55/100
Learning value58/100

Confirm eligibility and time commitment before moving into formal preparation.

Entry eligibility needs official confirmation

Open official pageSign in to saveOpen guide

Timeline

Registration opens
Sep 13, 2026
Registration deadline
Sep 17, 2026

Data and review state

Separate what is confirmed from what still needs review. Official rules and deadlines win.

View data stateClose
Source page verifiedMetric confirmedReviewed
Source published
Sep 14, 2026
Published on this site
Sep 23, 2026

Official metric is not published on the ModelScope 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.