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Gensokyo Densetsu[Chinese Version]

Gensokyo Densetsu[Chinese Version]

A Roblox experience owned by Unicorn Game Studio.

RacingZHTouhou ProjectRPGChinese Version

Description (written by the developer; not a statement by this register)

Gensokyo Densetsu is an RPG game of Touhou Project from JP. This version is a Chinese Version! ! PC Recommended ! 🔥New Content🔥 - Scarlet Devil Mansion & Alice Mansion - Marisa's Missions - Marisa Role & Weapons - Fumo & Inventory - Badges & Boosts - More NPCs ⚔️Operations⚔️ Dodge R Skills F/G/C/V/B Healing H (Equip in inventory first) CODEs Version1.3 A1FTGB ⭐Join our group for in-game Jades rewards: https://www.roblox.com/groups/7307713/Unicorn-Game-Studio 🌐Inspired by ZUN's Touhou Project Next New Version 1.4.0 (In Progress Now, Released By the End of July) - Konpaku Youmu BOSS Fight - New Role Suika & Youmu - Global Weather

Last updated by the developer 16 Oct 2025, 14:03 UTC.

0
playing (measured 10 Aug 2026, 18:47 UTC)
284,113
lifetime visits
78%
liked (1,393 👍 / 401 👎)
1,998
favourites (7.0 per 1k visits)
21 June 2021
created (per Roblox)

Play on Roblox →

Live players over time

Growth

Growth history is still building. We hold one measurement for this entry. A trend needs at least two, taken days apart — so this will fill in on its own rather than being estimated. We do not publish numbers we have not measured.

Measurement log — every players count we have recorded
Measured (UTC)PlayersChange
10 Aug 2026, 18:470first reading

Concurrent players at each of our measurements (insert-on-change).

Monetization — game passes

【半价优惠】双倍经验&信仰
249 R$
【半价优惠】双倍阴阳玉
199 R$
【半价优惠】双倍金币
199 R$

Game passes for sale and their prices, measured from the Roblox passes API. Developer products bought inside the game aren’t publicly listable.

Badge funnel

南瓜节?南瓜劫! · other6,681 · 0.00% win

How many players have ever earned each badge — a proxy for how far players get before they stop. Steep drop-offs mark where a game loses people. Win rate is the past-day share of players who earned it; categories are assigned by a language model from each badge’s own name and description.