
Wandering Sword is a Chinese martial-arts RPG where you play a young swordsman caught up in a feud and nearly dies. Escaping the event puts you on the path of pursuing the highest form of martial arts and exploring the pugilistic world to become the great hero you are always destined to be.
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About


Journey through over 75 breathtaking locations across 5 diverse regions, each echoing the richness and allure of ancient China's tradition and landscape. Explore a world filled with bustling ancient Chinese towns, scenic mountains, picturesque rivers, dangerous lairs, treacherous terrains and more!


Utilizing Unreal Engine 4, Wandering Sword portrays a captivating blend of traditional pixel art graphics seamlessly layered onto immersive 3D landscapes. Drawing upon the charm of classic pixel-based martial arts games, the game infuses modern visual effects to elevate every moment in its Wuxia world.


Wandering Sword introduces an innovative combat system that operates on a tiled board and offers players the flexibility to switch between turn-based and real-time mode. This dual mode approach caters to both traditional RPG players who prefer a slower pace and those who enjoy real-time action that demands quick reflexes.


Wandering Sword brings to life a diverse array of martial arts moves and weaponry. As you traverse the land, you'll unravel hundreds of martial arts techniques and weapon styles. Cultivate your energy through meridian points, gain expertise in both external and internal forms, and achieve true mastery of martial prowess.


In Wandering Sword(逸剑风云决), building relationships with NPCs is an integral part of your journey. Recruit up to 14 unique martial artists to join you on your adventures, each with their distinctive abilities. Who knows, you may even find love in this intricate world of martial arts!


Delve into an immersive Wuxia adventure with Wandering Sword. Boasting multiple endings shaped by your choices you make and a plethora of side quests that supplement the main storyline, enjoy over 20 hours of engaging gameplay that promises high replayability and a fresh experience with each adventure.

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Stats
All-time low is the lowest price we've recorded for this game since we started tracking it.
Languages: Simplified Chinese, English, Traditional Chinese
Updates
Build ids and update times come straight from Steam's PICS — the same source SteamDB reads. Patch history grows as we record new builds.
Engagement
Hours played at review time, across 681 reviews with recorded playtime.
Reviews
Themes across 681 recent reviews and how positive each mention is. A keyword signal, not full sentiment analysis.
positive critical· bar length = how often the theme comes up
Reviews
最好的武侠游戏
优秀的剧情和曾出不穷的新鲜奇遇,让人重拾儿时游玩rpg游戏的快感,近几年的jrpg有这感觉的只有神之天平和逸剑风云决,毫无疑问的武侠品类必玩之作。
让我又体会到了高中不眠不休看金庸的那些日子
好玩
看到不少人诟病剧情台词中二,作为一个没怎么看过武侠小说的人来说剧情倒是挺精彩的,不过最后的两国大战有草草收尾之嫌。可惜本来觉得欧阳雪应该是第一女主,但是塑造上反而走的是安全但平庸的路线。虽然作为男性玩家为主的游戏免不了后宫之类的设定,不过其他几个女角色的塑造也能看到亮点。免不了俗地还是感叹”妖女“吸引人。另外看到最后上官虹成为坊主收留孤苦女子,一下子想到《投靠女与出走男》里的东庆寺……
太好玩了,满足你对武侠的大部分幻想,虽然还是有些不自由,但是非常精美
夯!!自从学生时代后。很久没有这么沉迷一款游戏了。剧情也不错。人物刻画丰满。但最后结局太仓促了。感觉天山和玄火教剧情太仓促了。恒王的剧情也少很多。没有讲清上一代的故事。而且结局后没办法玩养老。这是对我的一点遗憾。
好!
圆了我的武侠梦
二周目通关碎碎念 一场美好的武侠梦,心中有诸多感想,却不知道该从何说起,一个因风云决而起的故事,说多了会剧透,说少了不知道该说啥。 每个npc的塑造都有自己的特色,有让人记忆的点,各自的故事有悲伤、有深沉、有欢乐、有牵挂、有遗憾、有释然。游戏里有着相当多的支线以及不同选择导致的剧情差分,一周目的时候自己摸索着玩,有些支线很容易断掉,使得最终的结局不够圆满,二周目照着攻略一步步的走,看着熟悉的剧情逐渐开始变得与一周目相比更加圆满,心中真的是万分欢喜。 大量的支线让剧情变得充满活力,人物塑造更加丰满,一周目探索地图时突然触发的支线让人惊喜,但是一些支线对剧情的提示不够明显,不过后来二周目的时候感觉这样安排挺好的,只按照任务提示进行任务是一种剧情,发现对话中潜藏着的信息(这些信息有的也会用颜色标注出来)去对任务进行补充是另一种剧情,如果是自己发现了隐藏的剧情,是真的很开心。 剧情的主线支线有江湖琐事、有行侠仗义、有爱恨情仇、有家国情怀,让人沉浸其中,最后结局看着那一幕幕的后日谈,让人感慨,这一切都是值得的,都是有所回报的,
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Trends
Modeled estimate over time, reconstructed from Steam's monthly review histogram.
Engagement
DAU/MAU are modeled from peak concurrent players (≈×8 and ×28) — Steam publishes no active-user counts, so treat these as rough estimates, not reported figures.
Audience
Estimated from the language of this game's reviews — a proxy for where players are, not official Steam demographics.
Audience
Games most often reviewed by the same players — an audience-affinity signal from our review sample, not full ownership data.
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