接棒$CARDS?详解宝可梦卡牌 RWA 交易平台 Phygitals

深潮Published on 2025-09-14Last updated on 2025-09-15

Phygitals 能否将宝可梦卡牌的火爆带到加密世界之中?

撰文:伞

在过去的半个月内,宝可梦卡牌RWA赛道的热度暴涨,其根源正是宝可梦卡牌链上交易平台Collector Crypto的代币CARDS在两周内实现了接近十倍涨幅。

9月初CARDS以0.04美元价格发行,近几日价格持续突破新高一度逼近0.4美元,完全稀释估值超过6.68亿美元。

如此迅速的涨幅也将宝可梦卡牌RWA这一小众赛道推向聚光灯之下,而结合了拆盲盒和宝可梦IP情怀的卡包机制也引发了市场的FOMO,根据Dune数据,过去一周内TCG(集换式卡牌)赛道内前四名平台销售卡包收入高达3100万美元。

而就在最近,同为宝可梦卡牌RWA赛道另一平台Phygitals引发了市场的关注与讨论,并且Phygitals近期的一系列动作似乎也在暗示即将发币,而错过CARDS也让很多投资者将希望寄托在了Phygitals上。

拒绝VC的加拿大创业项目

从黑客松原型到经历市场验证获得认可,Phygitals似乎一直带着一种与众不同的风格。

Phygitals最早可以追溯到2023年1月的Solana黑客松,创始人“Mister Colada”提出了“代币化交易卡牌市场”概念,经过近两年打磨后,2024年2月正式上线公测版本,同年3月卡牌交易市场开始运营。

不同于大部分加密项目在早期就开始寻找VC机构融资,Phygitals团队坚持零外部融资的路线。并且该项目团队曾多次在公开场合强调自己不需要VC和融资。

这种充满理想主义的坚持既避免了VC带来的清算压力,也保持了项目的纯粹性。但同时也意味着其增长完全依赖于现金流。好在从当前的热度来看,Phygitals团队的坚持获得了回报——根据DeFillama数据,Phygitals平台过去两周内仅手续费收入超过240万美元。

全新卡牌收藏体验

Phygitals官网链接

Phygitals的产品核心是将传统开卡包的过程完全数字化,保证数字卡牌一比一对应实物卡牌并且拥有充足的二级市场流动性。开卡包获取的宝可梦NFT支持兑换对应的实体卡牌,也可以在二级市场流通,消除了传统卡牌交易的低流动性、高物流成本和验证真伪难题等。

用户可以在Phygitals平台内选择不同价格的卡包进行开启,分别为1美元、25美元、50美元、80美元和250美元,越贵的卡包获取稀有卡牌的概率越高。由于其近期的火爆,当前80美元卡包甚至已经显示“脱销”状态。

Phygitals最大的创新在于其支持用户将开包获得的卡牌直接以当前市场公允价值的85%-90%进行即时回购,这一机制为卡牌交易市场引入了类似做市商的流动性机制,一举解决了困扰NFT市场已久的流动性难题。

当前Phygital支持用户在开包后30分钟内按照公允市场价值的85%-90%卖给平台,未来Phygitals计划将回购窗口延长至7天,这个设计也让数字卡牌具备了接近同质化代币的流动性。

除此之外,Phygitals近期也预告即将进入自己的“第二阶段”,在其官网和推特所展示的内容中可以发现,后续Phygitals或许将重点开展社交版块,上线直播等功能,让更多用户可以观看主播开卡过程并尝试亲自购买拆包体验。

从这一系列机制设计中不难看出,Phygitals将很大的精力放在了“流动性”上,为所有“拆包”用户提供放心的回购机制和流动性,无疑可以让更多卡牌爱好者打破顾虑来购买卡包,而卡包自带的盲盒属性叠加一代人心中宝可梦IP的情怀价值,更让无数用户陷入FOMO,乐此不疲地开卡并在社交平台上展示形成病毒式营销。

发币在即?如何获取空投预期

虽然Phygitals尚未发布任何代币经济学等信息,但多重信号似乎表明其代币发行正在筹备中。

9月12日,Phygitals发布了一条推文暗示“大的要来了”。

结合此前上线的开卡包获取对应积分机制,以及团队暗示积累的积分和持有Phygitals发行的NFT可能获取未来奖励。大量用户猜测Phygitals即将发币,而这样的讨论也吸引了一批错过了CARDS十倍涨幅的用户加入到Phygitals的拆包大军中,试图抓住这个赛道的另一头部标的。

当前阶段,用户可以通过购买Phygitals官网中“Packs”界面不同价格的卡包获取不同的积分奖励,购买每个卡包可获得相当于其价格一百倍的积分。

考虑到不同等级卡包开出的卡牌等级概率不同,以及Phygitals的回购机制,如果想要获取积分兑换未来的空投预期,当前选择50美元或80美元的卡包综合性价比较高,当然开卡包也是开盲盒的过程,有极小概率获取高等级稀缺卡牌,更大的概率则是获得普通等级卡牌由平台进行回购。

根据部分用户开卡包经历,25美元卡包开包后获得的普通等级卡牌回购价格大约是13-25美元,其中低等级的卡牌可选择自动由平台按照公允价值85%价格进行回购,稍高等级的卡牌需要点击确认回购价格。不过由于卡包开出卡牌等级具有随机性,这个数据仅可作为参考。

虽然一系列动作似乎都在表明Phygitals大概率即将发币,但当前其代币发行仍属于推测性质,各位投资者需要注意拆卡包具有极强不确定性。

市场反馈的两面性

当前市场对Phygitals的反馈呈现明显的两极分化,既有开出高价值卡牌的兴奋,也有对其卡包概率真实性的质疑。

其中积极反馈主要集中在其流动性和实物卡牌兑换上。Phygitals坚定支持者@Legendarygainz在推特晒出他在Phygitals上开出了价值3000美元的错版卡牌,证实Phygitals的卡包仓库中存在高价值卡牌的真实性。

另一位宝可梦卡牌收藏家@pominik则晒出自己在Phygitals将抽中的数字卡牌兑换为真实卡牌过程非常顺利。

而市场中对Phygitals的批评声音主要指向其概率透明度问题。部分用户反馈在高端卡包中重复抽中低价值卡牌,暗示其可能存在算法偏向等问题。同时推特平台内出现大量用户在相同时间开出同一张卡牌,被市场质疑其可能与平台进行合作,通过相同素材进行虚假营销。

总体来说,当时市场中对Phygitals看好的声音占据半数以上,大部分用户以及KOL认为Phygital可以接棒CARDS,让市场FOMO情绪更上一个台阶。

Phygitals当前站在一个万亿级收藏品市场和新兴RWA赛道的交汇点,虽然面临着诸多质疑,但不可否认的是当前市场中已经掀起了拆卡包的FOMO情绪,在笔者身边也有很多朋友愿意花几十美金去享受这个拆盲盒的过程。

无论是Collector Crypto,还是Phygitals,都将宝可梦卡牌与加密技术实现了良好的融合,而在CARDS之后,有更多卡牌RWA交易赛道内外的用户正焦急等待着下一个机会,让我们共同期待,看Phygitals能否将宝可梦卡牌的火爆带到加密世界之中。

Related Reads

τ Scaling: Huawei's New Growth Engine Designed for the Post-Moore Era

**Tau Scaling: Huawei's New Growth Engine for the Post-Moore Era** For 60 years, progress in semiconductors was driven by Moore's Law – making transistors smaller, denser, and cheaper. This path has now stalled due to plummeting returns below 7nm, astronomical lithography costs, and rising per-transistor expenses. After six years and testing 381 production chips, Huawei’s semiconductor team proposes a fundamental shift: **stop competing on size, start competing on time**. This is the core of their "τ (Tau) Scaling" theory. It treats *time* as the key optimization metric, compressing characteristic delays (τ) across all levels – from transistor switching (picoseconds) to data center tasks (seconds), spanning 12 orders of magnitude. **What is τ Scaling?** It holistically minimizes delay/time constants (τ) across four layers: transistors (switching speed), circuits (signal delay), chips (compute/memory access), and systems (end-to-end communication). The goal is to align optimization from process and circuit design to architecture and systems using this unified metric. **Mobile Application: LogicFolding** Without advancing the process node, this technique vertically stacks chips using ultra-precision hybrid bonding, distributing critical paths across layers ("stacking floors"). Results include a 55% transistor density increase, 41% better energy efficiency, over 40% higher SRAM frequency, and a roadmap targeting 4GHz by 2029. **AI Data Center Application: Full-Link Latency Compression** With 80% of AI cluster energy and 70% cost spent on data movement, the focus is slashing communication time. Key innovations include: 1. **Unified Bus:** Cuts multi-layer protocols, reducing remote access latency from microseconds to ~100 nanoseconds – 500x faster. 2. **Hi-ONE Optical Interconnect:** Replaces copper with fiber, enabling 8Tb/s per module and scaling distances from 1m to 100m for 10,000-chip clusters. 3. **3D Folding:** Solves the "interface bottleneck" of 2.5D packaging by vertically integrating memory, power, and optical I/O alongside compute, predicting over 100x integration density gain by 2035. **Re-fusion of Logic and Memory** The AI era, where data movement is more critical than computation, demands tight 3D integration of logic and memory, shifting industry influence towards memory and advanced packaging. **Remaining Challenges** include adapting EDA tools for 3D design, optimizing wafer-to-wafer process variation and vertical interconnect losses, and establishing new energy efficiency and benchmarking standards. **Conclusion:** The era of scaling physical dimensions is over. The era of scaling time has begun. By leveraging 3D stacking, system architecture, and interconnect optimization—rather than solely chasing advanced lithography—performance and efficiency can continue to advance. This is poised to be the semiconductor industry's core roadmap for the next decade.

marsbit8m ago

τ Scaling: Huawei's New Growth Engine Designed for the Post-Moore Era

marsbit8m ago

NodeStrategy: The First Ordinals DAT Project, Bringing the Strategy Treasury Narrative to NFTs

**Summary: The Fundamental Flaws of NodeStrategy, the 'First Ordinals DAT'** NodeStrategy presents itself as the first Ordinals Digital Asset Treasury (DAT) on Bitcoin. Its model mirrors MicroStrategy's treasury narrative but for NFTs, specifically targeting the NodeMonkes collection (not officially affiliated). The project's core mechanism is a four-step flywheel: a 10% fee on all trades (90% to treasury, 10% to radFi/Bound marketplace) is used to buy NodeMonkes. These NFTs are then listed for sale on Satflow, with 100% of the sale proceeds used to buy back and burn the project's token, NODESTRAT, aiming to create a perpetual value cycle. However, the design contains critical, self-defeating flaws: 1. **Platform Lock-In:** As a Bitcoin Rune, NODESTRAT lacks smart contract functionality and cannot natively enforce the 10% fee. The fee can only be collected on the radFi/Bound marketplace itself. This makes the entire flywheel dependent on a single platform. If liquidity moves elsewhere, fee revenue drops to zero, halting the mechanism. 2. **Self-Suffocating Economics:** The 10% fee acts both as the flywheel's fuel and a major drag on demand. A buy/sell roundtrip incurs a 20% cost, creating a massive hurdle for traders. This strangles the very trading volume needed to generate fees. 3. **Ineffective Value Support:** The flywheel is starved. Low daily volume (~$9K) generates minimal fees for NFT purchases. The NFT "ladder" sales are slow and unpredictable (only 39 total sold), meaning buybacks are infrequent. While 30.77% of the supply has been burned, this supply reduction cannot lift price without corresponding demand, which is suppressed by the high transaction tax. 4. **Meaningless NAV:** The Net Asset Value (NAV), currently at a 0.46x discount to market cap, is merely a marketing figure. There is no redemption mechanism for token holders to claim the underlying NodeMonkes assets. Price is set by market liquidity flows, not by this theoretical backing. In essence, NodeStrategy's design forces its revenue source (trading fees) to simultaneously cripple the demand and liquidity required for its own success, trapping the project in a stagnant state.

marsbit14m ago

NodeStrategy: The First Ordinals DAT Project, Bringing the Strategy Treasury Narrative to NFTs

marsbit14m ago

Agentic Design Patterns: A Book That Made Me Re-Understand "What Is an Agent, Really?"

"Agentic Design Patterns" is a 2025 book by Antonio Gullí, a Google engineering director, which offers a systematic framework for AI Agent development through 21 design patterns. A core contribution is the "Four Levels of Agency": Level 0 (bare LLMs) are not true agents. Level 1 agents actively decide when and how to use tools. Level 2 agents engage in strategic planning, context engineering (curating and filtering information), and self-reflection. Level 3 involves multi-agent collaboration with defined communication topologies. The book introduces **Context Engineering** as a superset of prompt engineering, managing four layers of information for the agent: system prompts, external data, implicit context (user history, environment), and feedback loops for automated optimization. A key pattern is **Reflection (Producer-Critic)**, where two distinct agents with different prompts collaborate iteratively—one produces output, the other critiques it—until quality is satisfactory or a max iteration limit is reached. For **Memory**, a three-layer model is proposed: Session (ephemeral conversation context), State (temporary task data), and Memory (persistent, long-term storage). Regarding **Multi-Agent Systems**, the book advises against unnecessary complexity, recommending simple topologies like Supervisor or Peer-to-Peer based on task needs. It emphasizes perfecting a single Level 2 agent before moving to multi-agent setups. The author concludes with three actionable takeaways: 1) Add a Critic agent to existing workflows, 2) Practice Context Engineering beyond simple prompts, and 3) Avoid premature multi-agent complexity; first master a robust single agent. The book provides a practical map, codifying common challenges like reflection, memory, and coordination into reusable patterns, saving developers from reinventing foundational solutions.

链捕手1h ago

Agentic Design Patterns: A Book That Made Me Re-Understand "What Is an Agent, Really?"

链捕手1h ago

An AI Read SpaceX's Prospectus and Wrote This Investment Memo in 12 Minutes

An AI agent autonomously analyzed SpaceX's 226MB S-1 filing, purchased real-time market data on-chain for $1.87, and generated a comprehensive investment memo in 12 minutes. The memo concludes a "Hold" recommendation. Bull Thesis: SpaceX holds a near-monopoly in commercial launch (80% of global orbital mass since 2023), operates the profitable Starlink business (10.3M subscribers, $7.2B adj. EBITDA), and is vertically integrated from rockets to AI via the xAI acquisition. Starlink alone is a standout, high-margin business. Bear Thesis: The AI division is a massive cash burn ($6.4B operating loss on $3.2B revenue in 2025). True debt obligations approach ~$42B, not the headline $29B, due to bridge loans and X-related debt. Significant contingent liabilities exist, including a potential $10B fee from a Cursor option agreement. The company faces concentrated counterparty risk (e.g., a $45B Anthropic contract), slowing revenue growth, and complex governance as a controlled company with four share classes. Valuation anchors Starlink's standalone value at ~$84B (applying Iridium's 7.4x sales multiple), suggesting the current ~$500B+ IPO target prices in immense future execution risk for Starship and AI. Key risks include Starship delays, accelerating AI losses, and underwriter conflicts (the IPO's lead banks are also lenders on the $20B bridge loan it aims to refinance). Investment triggers: upgrade to "Overweight" if priced ≤$350B and Starship meets milestones; downgrade to "Pass" if priced >$510B or key risks materialize.

marsbit1h ago

An AI Read SpaceX's Prospectus and Wrote This Investment Memo in 12 Minutes

marsbit1h ago

Trading

Spot
Futures
活动图片