个股论点
围绕单一股票的投资逻辑与仓位表态 · 共 2378 条 · 滚到底自动加载更多
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对比特斯拉与NBIS在自动驾驶出租车领域的估值差异。
@longinvest32 $TSLA 的 FSD（完全自动驾驶）L2 级 Robotaxi（自动驾驶出租车）——市场基于 1 万亿美元以上的估值，增加了约 3000 亿美元的市值。 $NBIS 的 FSD L4 级 Robotaxi——市值 230 亿美元，盘前下跌 1.3%。
英文原文
@longinvest32 $TSLA FSD level 2 robotaxis -> market adds ~$300B off a $1T+ valuation. $NBIS FSD level 4 robotaxis -> down 1.3% premarket off a $23B marketcap.
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Uber整合NBIS自动驾驶出租车，有望加速规模化并降低成本。
这对 $NBIS Avride 来说太棒了，看看 $UBER 是怎么做的。据我了解，其运作方式是：当用户通过 UberX 等常规服务叫车时，系统会匹配 $NBIS Avride 的 Robotaxi（自动驾驶出租车）供 $UBER 用户选择。这对规模化至关重要，因为用户无需像选择 UberX Black 那样额外付费去专门寻找自动驾驶服务。初期车内仍有人类驾驶员监控，但随后会像 Waymo 一样逐步取消。如果进展顺利，$UBER 可以扩大其 Robotaxi 网络并节省人类司机成本（这也利好 $NBIS）。
英文原文
So this is amazing for $NBIS Avride how $UBER is doing it. How it works from what I understand is when someone requests a ride with ubebx and the usual, they get matched a $NBIS Avride robotaxi pickup from $UBER and have the option. (this is huge for scale since it's not going out of the way to select a separate robotaxi section for more cost like uberx black). There's a human behind the wheel at the start, just to monitor if things go well. But they'll be phased out like Waymo. IF this works out well, $UBER can ramp up their robotaxi network and save the costs of human drivers (and this benefits $NBIS too).
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Nebius因算法忽视其高增长子公司而被严重低估。
不，这对 $NBIS 来说甚至算不上新闻。 就在刚才，Avride 与 $UBER 的合作发布可能是该投资组合公司十年来最大的头条，但在 $GOOGL / $HOOD 等新闻聚合器（算法也依赖这些）上，这甚至与 Nebius 不相关。 这就是为什么我一直认为 Nebius 在结构上被错误定价和误解，因为有像 Avride 这样 4 家同比增长 100%+ 的子公司，但市场/算法并没有将这些动态部分纳入定价。
英文原文
Nope, it’s not even news for $NBIS. Just now, Avride launch with $UBER is probably the biggest headline of the decade for the portfolio company but its not even correlated to Nebius on places like $GOOGL / $HOOD news aggregators (which algorithms rely on too) This is why I’ve been arguing Nebius is structurally misvalued and misunderstood because there’s 4 subsidiaries like Avride growing 100%+ Y/Y but markets/algorithms aren’t pricing in the moving parts
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Nebius子公司Avride联手Uber在德州推出L4级Robotaxi，开启商业化。
最新消息：Nebius [ $NBIS ] 的 FSD 4 级 Robotaxi（自动驾驶出租车）子公司 Avride 已与 $UBER 合作在德克萨斯州正式推出。 自 2017 年经过近十年的开发，Avride 终于将其自动驾驶汽车技术投入全面商业运营。 https://t.co/DSPRvmNw3f
英文原文
Just in: Nebius [ $NBIS ] FSD level 4 Robotaxi subsidiary Avride has now launched in Texas in partnership with $UBER. After nearly a decade of development since 2017, Avride is finally taking its self-driving car tech into full commercial operation. https://t.co/DSPRvmNw3f
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IREN股价因吉姆·克拉默的言论获救。
@cronked 看起来 $IREN 被吉姆·克拉默（Jim Cramer）救了。
英文原文
@cronked Looks like $IREN got saved by Jim Cramer
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对比NBIS与IREN融资稀释影响，指出DC建设需购GPU导致稀释不可避免。
关于 $NBIS，时机确实是个巨大因素，他们在宣布 $70-$90亿 ARR（年度经常性收入）后进行了操作。此外，MSCI 的资金流入也抵消了大部分稀释，下个月可能还会纳入纳斯达克100指数。 对于 $IREN，我目前的观点是：如果他们想通过拥有 GPU 的 AI 云（AI Cloud）变现其巨大的算力容量，就需要进行大量稀释。这不仅仅是“拥有 3GW 容量 x 一定收入”那么简单，当他们不做托管（Colocation）业务时，还需要购买 GPU。 现有股东/市场可能不喜欢这一点。特别是仅针对 $MSFT 的交易，硬件成本就高达约 $58亿（如果我记得没错的话）。虽然他们获得了预付款，但仍需筹集更多资金。 长期来看这是净正面的，但任何当前持有者都会感到痛苦。 即使是 $NBIS 的融资，我也非常不喜欢稀释，希望他们通过运营利润来融资剩余部分，但这是数据中心（DC）建设的现实。Nebius 起初就有更大的现金储备（坐拥 $48亿+），相比 $IREN 他们受到的冲击稍小一些，但让我们看看会发生什么。
英文原文
With $NBIS yeah timing was a huge factor that they did it after announcing $7-$9B ARR. They also had MSCI inflows to offset a lot of the dilution too and maybe nasdaq100 next month. For $IREN my opinion so far is that if they wanted to monetize their immense of capacity in their AI cloud with GPUs, there needs to be a ton of dilution. It's not just oh we have 3GW capacity x amount of revenue, they need to buy the GPUs too when they're not doing colo. Existing shareholders/markets probably don't like that. Especially with spending ~$5.8B in hardware costs (if i remember correctly) for the $MSFT deal alone. They got pre-payment but they still needed to raise more. Long term it's net positive but anyone holding now would feel a lot of pain. Even for $NBIS raise I really disliked dilution and wanted them to finance the rest through operational profit, but that's the reality of the DC buildout. Nebius already had a bigger cash pile to begin with (was sitting on $4.8B+) compared to $IREN, so they're a tad more isolated but we'll see what happens.
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认为SMCI 12/12到期31美元看跌期权走势稳健
@dubiousnoob $31 $SMCI 12/12 看跌期权(put) 看起来相当稳健
英文原文
@dubiousnoob $31 $SMCI Put 12/12 seems pretty solid
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谷歌太空数据中心项目利好 Planet Labs 及发射商 Rocket Lab。
谷歌($GOOGL) CEO 近日发布：Project Suncatcher 项目，计划于 2027 年在太空建立数据中心。下一代张量处理单元(TPU)将运行在太阳能卫星星座上，以扩展机器学习(ML)流程。最大的受益者是谁？Planet Labs ($PL) 以及衍生的 $RKLB 和 SpaceX。Planet Labs 是一家鲜为人知的小市值($35亿)太空公司，凭借此交易拥有巨大上行空间。Planet Labs 将为谷歌部署两颗原型卫星，目标是在 2027 年初发射。$PL 使用的发射服务商是 $RKLB（分别于 2018 年 1 月和 2020 年 10 月）和 SpaceX。其中一家（Rocket Lab）让人想起我最高确信度的多头持仓。对于 $PL 而言，收入可能在 1000 万至 4000 万美元的小范围内。但如果原型机顺利，完整的星座将带来 2.5 亿至 10 亿美元以上（且规模效应下更多）的收入。你搭上 $GOOGL 供应商列车了吗？
英文原文
Google ( $GOOGL ) CEO recently unveiled: Project Suncatcher, a project to create datacenters in space in 2027. Next generation TPUs will run on solar-powered satellite constellations to scale ML flows. The biggest beneficiary? Planet Labs ( $PL ) and by derivative $RKLB and SpaceX. Planet Labs, a lesser known, small cap $3.5B space company, has huge upside with this deal. Planet labs will deploy two prototype satellites for Google, targeting a launch by early 2027. The launch providers that $PL uses are $RKLB (January 2018 and October 2020) and SpaceX. One of which (Rocketlab) reminds one of my highest conviction longs. For $PL revenue is likely in the small $10-$40M range. But a full constellation would bring in $250 million to $1 billion+ (and more at scale) if the prototype goes well. Are you riding the $GOOGL supplier train?
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SMCI因远期增长定价偏差适合交易，非长期投资首选。
@MajorOcelot45 对我来说，$SMCI 是一只用于交易的股票，因为其远期增长存在定价偏差，市场上有大量更好的长期投资标的。
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@MajorOcelot45 For me $SMCI is a stock to trade due to mispricing of forward growth, there’s tons of better long term investments.
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承认对方对IREN的研究，指出与NBIS估值标准化存在分歧。
@Agrippa_Inv @RJCcapital @MarkosAAIG @moninvestor @pepemoonboy @DeepValueBagger @amitisinvesting @Sandeman52 不，说真的，我相信你们为 $IREN 制作了很好的内容，并且更了解那家特定公司。我认为我们在 $NBIS 的指标标准化(normalizing figures)问题上存在分歧。
英文原文
@Agrippa_Inv @RJCcapital @MarkosAAIG @moninvestor @pepemoonboy @DeepValueBagger @amitisinvesting @Sandeman52 nope, in all seriousness, I'm sure you produce good content for $IREN and know more for that specific company. i think we just come to a disagreement when it comes to to normalizing figures vs. $NBIS lol
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对比NBIS的高增长潜力与SMCI的估值修复机会。
所以是不同的股票组合。我会这样解读： - $NBIS：高贝塔值，超高速增长，未来走向难料。潜在上行空间最大（核心业务同比增长700%，Robotaxi FSD部门等4家子公司同比增长100%+）。 例如，如果$UBER本月在德克萨斯州与Avride合作的Robotaxi（自动驾驶出租车）发布顺利并扩展至其他地区，我们可能会看到该子公司估值大幅上升。 - $SMCI：盈利，估值修复带来中等回报（仍有~30-60%的回报空间）。同比增长60%，但远期市盈率仅为11倍，像$PYPL这样的零增长股或像$MSTR这样的困境资产。 对于SMCI，更多是看数据和行业，发现错配（例如$UPWK的价值投资逻辑）。
英文原文
So different basket of stocks. How I'd frame it is: - $NBIS: high-beta, hyper growth, who knows where it goes. Highest possible upside (700% Y/Y core business, 100%+ Y/Y across 4 subsidiaries like Robotaxi FSD division). For example if $UBER Texas robotaxi launch goes well with Avride this month and they expand elsewhere, we could see the subsidiary valuation rise a lot. - $SMCI: profitable, moderate return from valuation catchup (still ~30-60% return). Growing 60% Y/Y but priced at 11 forward p/e like a no-growth stock eg. $PYPL / distressed asset like $MSTR. For SMCI it's more about looking at the numbers/sector and seeing a misalignment (eg. $UPWK value investing)
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看好$LITE因TPU放量潜力，虽追高但仍决定定投建仓。
有点遗憾我加入 $LITE 派对晚了，它现在正处于历史高点(ATH)。但如果看看 $NVDA 从2022年到现在发生了什么，如果张量处理单元(TPU)最终成为推理领域的主导力量，同样的情况也可能发生。而且，$LITE 与 TPU 的放量直接相关。遗憾的是，我此前没有意识到它对生态系统有多么关键。这是我正在通过成本平均法(Cost Averaging)建仓的标的，虽然有点晚，但很高兴将其加入我的投资组合。
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Yeah little sad I'm late to the $LITE party and it's ATHs right now. But if we look what happened to $NVDA 2022 to now, same could happen if TPU ends up becoming a dominant player in inference. and.. $LITE is directly correlated to TPU ramp up. Sadly didn't realize how vital it was to the ecosystem earlier. This is something I'm cost averaging shares with but it's a happy add to my portfolio.
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CoreWeave CEO称其自研软件栈是核心竞争优势。
对于 $CRWV，其CEO表示，正是其软件编排(software orchestration)能力，使他们能够将裸机(bare metal)转变为功能完备的超级计算机。CNBC上有一段5分钟的采访涉及此话题。 另一段采访： “CEO强调了CoreWeave的定制软件栈(custom-built software stack)，他认为这将在长期使公司脱颖而出。他表示：‘从我们的角度来看，我们真的相信，随着时间的推移，将我们与他人区分开来的……是驱动我们在基础设施上实现性能的……软件栈。’ Intrator补充说，CoreWeave的软件栈是从零开发的，以优化为指导原则。”
英文原文
For $CRWV its software orchestration according that allows them to turn bare metal into fully functioning supercomputers to their CEO. There’s a 5 min CNBC interview on this Another interview: “The CEO highlighted CoreWeave’s custom-built software stack, which he believes will set the company apart in the long run. He stated, “From our position, we really believe that over time, what’s going to differentiate us from anyone else is the … software stack that drives the performance that we’re able to achieve on our infrastructure.” Intrator added that CoreWeave’s software stack was developed from scratch, with optimization as the guiding principle. “
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CRCL暴跌主因是禁售期解禁与流通盘动态，而非仅因降息。
所以，这在一定程度上是正确的。然而我认为 $CRCL 下跌约 50% 的主要原因在于禁售期(lockups)和流通盘(float)动态，而不仅仅是利率降息。我们在 $BULL 首次公开募股(IPO)时就见过这种情况，其以 2% 的流通盘交易，市值一度超过 500 亿美元，但在禁售期结束后暴跌回 60 亿美元。据我记忆，$CRCL 仅以有限的流通盘（约 17%）进行交易，且最近又有 3400 多万股解禁。
英文原文
So, this is partially true. However I’d argue the main reason for $CRCL ~50% drop was lockups and float dynamics, not just rate cuts. We saw this with $BULL ipo where it traded on 2% float upward of $50B and crashed back to $6B post lockup. $CRCL was only trading with a limited float (~17%) if I remember correctly, and another 34M+ got unlocked recently.
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作者基于技术背景看空ETH，认为其核心机制恶化，同时提及BMNR。
诉诸权威的论证是最糟糕的，因为没有推理过程就毫无价值。以太坊尤其如此，当你看到其核心方面发生负面变化时更是如此（我们从分片(L1 Scaling)转向L2，$ETH代币也从因使用而增值的Gas费代币转变为治理/抵押品代币）。如果你想了解我的背景，我发明了如今大多数钱包使用可信执行环境(TEE)进行密钥签名的方法。我曾在加州大学伯克利分校研究过权益证明(DPoS)和秘密共享。所以我知道得足够多，可以发表评论。我们看看价格会怎么走，这是我个人看空的原因，人们可以自由地用他们自己的钱买入$BMNR并持有$ETH。
英文原文
Arguments from authority are the worst ones because they hold no merit without any reasoning. With Ethereum especially this is true when you see core aspects of it changing in a negative way (we went from L1 scaling with sharding -> L2s, and $ETH token going from a gas token that appreciated from usage to governance/collat). If you want my background though, I invented how most wallets nowadays do key signatures with TEEs. And I was a researcher in dpos + secret sharing back at UC Berkeley. So I do know a tiny bit enough to comment. We'll see where the price goes, it's my individual thesis on why I'm bearish, people are free to buy $BMNR and hold $ETH with their own money.
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以太坊L2降低费用削弱ETH通缩，作者看空ETH及BMNR。
这进一步印证了我的观点。L2（二层网络）的数据可用性（Data Availability）成本更低，虽有利于扩展性，但无法解决价值向 ETH 回流的问题。我一直认为以太坊实现了扩展，且是极佳的开发网络。但这以牺牲 $ETH 升值潜力为代价，因此我对 $BMNR 也持看跌态度。ETH 的 L2 构想最初对币价有利，因为稀缺的区块空间加上使用量上升形成了费用/销毁飞轮。但：Fusaka 升级 -> 更多 Blob -> 更便宜的数据可用性 -> 更低的 L2 费用。这对 ETH 的费用/销毁机制不利。此前 L1 使用带来的代币销毁是价格升值的首要机械驱动力（如 EIP-1559、合并 -> 通缩），但这已消失。除非情况改变，否则我会继续使用以太坊网络，但绝不会将其代币作为投资标的。
英文原文
So, that just reinforced my point more. L2s get even cheaper data availability, which is good for scaling but doesn't address value accrual to ETH. I've maintained Ethereum managed to scale. And it's a great network to develop on. But all that at the cost of $ETH appreciation, which is why I'm bearish also on $BMNR. ETH's L2 idea was originally good for ETH price because scarce blockspace + rising usage = fee/burn flywheel. But: Fusaka -> more blobs -> cheaper DA -> lower L2 fees. Not good for ETH fee/burn. Token burn from L1 usage was the #1 mechanical driver of price appreciation (eg. EIP-1559, Merge - > deflationary) before but that disappeared. Until that changes, I'll keep using Ethereum as a network but I will absolutely stay away from the token as an investment.
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ETH网络成功但代币逻辑弱化，对ETH及BMNR持看空观点。
$ETH 最初且简单的投资逻辑是：更多网络使用 -> 更多 Gas 需求 -> 更高的 ETH 价格。 正如你所说，在 L2 + Blobs/EIP-4844 之后，价值体现方式已不同。生态系统使用量 ↑↑↑，L1 Gas + 销毁 ↓。 这也是我对 ETH 作为代币/ $BMNR 作为投资载体持负面看法的原因。以太坊作为网络获胜（它确实赢了）与 $ETH 代币价格上涨是有区别的。 与现已消失的使用量带来的机械性上涨相比，抵押品等经济挂钩极其微弱。
英文原文
The original and simple investment thesis for $ETH was: more network usage -> more gas demand -> higher ETH price . As you mentioned this is no longer the case since value shows up differently after L2s + blobs/EIP-4844. Ecosystem usage ↑↑↑, L1 gas + burn ↓. And this is where I have a negative view of ETH as a token/ $BMNR as a holding vehicle for investment. There's a difference of Ethereum winning as a network (it did), and $ETH token appreciating in price. Economic hooks like collateral, etc. are extremely weak compared to mechanical upside from usage that is now gone.
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ETH网络增长但价值外流，L2导致销毁量低，高价下投资逻辑失效。
以太坊网络本身正在增长。但 Vitalik 扩展以太坊的方式将经济价值从资产本身推开了。 这就是让 $ETH / $BMNR 在 $4K 以上成为糟糕投资（尽管是好交易）的残酷经济现实。 L2 削弱了持有者的价值捕获，因为数据可用性(DA)和区块空间(blockspace)并非如此运作（10倍使用量 -> 10倍 DA 费用 -> 10倍销毁）。生态系统使用量创历史新高，但 $ETH 销毁量却处于历史低位(ATL)，这正是展示这种差异的关键指标。 压缩的低成本 Blob 意味着数十亿级的 L2 活动仅转化为极少量的主网 ETH 支出。 主网每天仅销毁数十枚 ETH，远低于 EIP-4844 之前的数百/数千枚。你说得对，L2 确实改变了 ETH 的价值捕获机制……通过将其移出 ETH。 你可以争论作为抵押品资产的投资选项和价值捕获的转移。但最初证明 ETH 作为投资合理性的主要代币经济学已不复存在： ETH 作为资产的价格不再与网络使用量成比例增长。
英文原文
Ethereum's network itself is growing. But the way Vitalik scaled Ethereum pushed economic value away from the asset. That's the sad economic reality that makes $ETH / $BMNR a terrible investment above $4K (it's a good trade). L2's weakened value accrual for holders because it doesn't work this way with DA and blockspace (10x usage -> 10x DA fees -> 10x burn). Ecosystem usage hits new highs, yet $ETH burn ATLs is exactly what you look at to show this disparity. Compressed, low-cost blobs mean that billions in L2 activity translate into only a tiny amount of ETH spent on mainnet Mainnet is burning tens of eth a day, down from hundreds/thousands a day before EIP-4844. You're right by saying L2s have genuinely changed ETH's value accrual mechanics... by moving it off of ETH. You can argue collateral asset as a investment option and a shift of value accrual. But the main token economics that originally justified ETH as an investment doesn't exist anymore: ETH price as an asset no longer scales proportionately with network usage.
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ETH因L2抽离价值致主网收入崩塌，代币缺乏投资吸引力。
最后，@VitalikButerin 完美指出了我对 $ETH 看空以及 @fundstrat 的 $BMNR 的原因。 $ETH 作为一种代币是极差的投资，尤其是在 $4K 以上时。 这是 Tom Lee、Cathie Wood 的 ARK 创新基金、Vitalik 等人没有理解的一点： 以太坊网络(Ethereum network)与作为实用代币的 ETH 之间存在脱节。 以太坊网络（正在增长）的增长并不转化为代币价格的上涨。 如果你在 2021 年底附近买入 $ETH，你会亏钱。与此同时，$BTC 的价格自那时以来上涨了接近 300%。为什么？ 二层网络(Layer 2s)。 1. Vitalik 在过去几年鼓励用户转向 L2（如 Base）。结果现在这些网络处理数十亿的交易量，但所有费用都流向了像 Coinbase（排序器 sequencer）这样的公司，而不是以太坊的验证者。 2. L2 支付存储数据的费用，但这与它们从以太坊主网(Ethereum mainnet)抽离的经济价值相比微乎其微。 就是这样。L2 抽走了利润和活动，而以太坊网络几乎收不到任何数据存储费。价值积累(Value accrual)流向了像 Coinbase 这样的公司，而不是 ETH 代币持有者。 以太坊网络使用量创历史新高，但主网收入崩溃，持有代币作为投资几乎没有经济激励。 除非有协议变更能从 L2 活动中为 ETH 代币产生合理的价值积累，否则不要将 ETH 作为投资。
英文原文
Finally, @VitalikButerin perfectly pointed out why I’m bearish on ETH, and @fundstrat’s $BMNR. $ETH as a token is a terrible investment, especially above $4K. This is what Tom Lee, Cathie Wood’s ARK innovation, Vitalik and others didn’t understand: There is a disconnect between Ethereum as a network and ETH as a utility token. Ethereum network (that’s growing) does not translate to the token price appreciating. If you bought $ETH near the end of 2021, you would have lost money. Meanwhile $BTC price has appreciated close to 300% since then. Why? Layer 2s. 1. Vitalik encouraged users to move to L2s (like Base) over the past few years. As a result now these networks move billions in volume but all fees go to companies like Coinbase (sequencer) not validators on Ethereum. 2. L2s pay fees to store their data but this is just incredibly minimal compared to the economic value they siphoned off of Ethereum mainnet. That’s it. Layer 2s siphoned off profit, activity, while the Ethereum’s network receives barely anything for data storage. Value accrual went to companies like Coinbase, not ETH token holders. Ethereum’s Network usage is at an all-time high, but Mainnet revenue has collapsed and there’s little economic incentive to hold the token as an investment. Unless there’s protocol changes that generate reasonable value accrual to the ETH token from L2 activity, don’t bother with ETH as an investment.
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IREN单季签约容量大增，展现强大执行力与护城河优势。
哦，看来 @babyfolio 已经替我回答了！ 从 1 GW 到 2.5 GW 的指导性签约容量（Guided Contracted Capacity），仅一个季度就实现这样的增长已经非常惊人。稍微调整一下大家的预期，GW 级容量是一道护城河（Moat），而 $IREN 在这道护城河上坚守了最长时间。 因此，能在短短一个季度内实现与 $IREN 的中长期对等，这表现堪称惊艳。 话虽如此，正如 babyfolio 所说，我认为 2.5 GW 这一数据已经大大超出了我的预期哈哈，但如果他们能在一个季度内实现 250%+ 的增长，他们可能再次做到。所以在这些情况下，你只需信任管理层的执行力（Management Execution）。
英文原文
oh looks like @babyfolio answered that for me! Going from 1 GW to 2.5 GW guided contracted capacity is already amazing from just 1 quarter. Just to tamper your expectations a bit, GW capacity is a moat and one that $IREN held for the longest time. So to achieve medium-long term parity with $IREN in just 1 quarter is spectacular. That being said, I think the 2.5 GW already kinda blew away my expections like babyfolio said haha, but if they're able to increase 250%+ in 1 quarter, they could do it again. So in these cases, you just trust in management execution.
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NBIS产能指引大增追平IREN，长期竞争力趋同
事实上，截至第三季度财报，$NBIS 将其签约产能指引提高了2.5倍，并在长期层面几乎追平了 $IREN。然而，$IREN 在前置并网产能（现在至2026年上半年）方面拥有巨大价值。但从2026年下半年起，$NBIS 在这方面似乎已迎头赶上（截至Q3，签约电力指引从3 GW调整为2.5 GW）。
英文原文
So actually as of Q3 earnings, $NBIS 2.5x'd its contracted capacity guidance and achieved near long-term parity with $IREN. However, $IREN has a tremendous amount of value in front loaded grid-connected capacity (now -> H1 2026). But H2 2026 onwards, $NBIS looks like it caught up in that front (3 GW to 2.5 GW contracted power guided as of Q3)
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回应反馈，重申对NBIS作为十年一遇机会的高置信度持仓逻辑。
感谢反馈，我会铭记于心，并照常发布其他主题的内容！ 我昨天发布了关于 $NVDA 等标的的深度研究(DD)，但正如你提到的，近期内容主要集中在 NeoCloud 板块。我之所以聚焦于此，是因为近期新闻密集，且巨大的抛售引发了大量关注！ 具体到 $NBIS，这是我持仓两年中信心最高的一笔投资。我认为这是继 $NVDA 之后十年来难得的机会，你很少看到一家核心公司净利润同比增长 700%，同时旗下 4 家投资组合公司净利润均实现 100% 的同比增长。 其中一家恰好是一家非常酷的自动驾驶 Robotaxi 公司（我是 Waymo 和 $TSLA Robotaxi 的粉丝）。
英文原文
Thanks for the feedback, I'll take it to heart and do posts on other stuff as usual! I posted DD about stuff like $NVDA yesterday but recently as you mentioned it's been mainly about the neocloud sector. I've been focused on it because of how much news there was recently + the huge sell off attracted a lot of attention! For $NBIS in specific, it was my highest conviction 2 year hold. I just see it as the opportunity of a decade since $NVDA, you don't really see any core company growing its bottom line 700% Y/Y with 4 separate portfolio companies growing 100% Y/Y. One of which happens to be a super cool self-driving robotaxi company (I'm a fan of Waymo, $TSLA robotaxis).
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重申看好IREN及新云板块，特别看好其高增长副业。
@babyfolio 自从我发布最初的论点帖子以来，我一直看好 $IREN 以及新云(neocloud)板块！ 我只是恰好对那家作为副业(side quest)拥有4家投资组合公司且同比增长100%+的企业极度看好。
英文原文
@babyfolio I've always been bullish on $IREN and the neocloud sector since my original thesis post! I just happen to be mega bullish on the one that has 4 portfolio companies growing 100%+ Y/Y alongside it as a side quest.
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澄清 $MSFT 交易估算差异及图表错误，确认 H100 数据有效。
你在 $MSFT 这笔交易上的看法是对的。我在托管设施(Colocation)方面使用了混合估算值，$NBIS 在其他地点拥有设施，但对于 $MSFT 这笔特定的独立交易，托管费会有所不同。此外，我在进行 GPU 标准化(GPU normalization)的不同对比时，用错了图表。右侧的 H100 标准化数据仍然有效。
英文原文
You're right on the $MSFT deal. I used blended estimates for colocation, $NBIS owns facilities in other location but for specific $MSFT deal standalone, the colocation fee would be different. Also was doing different comparisons for GPU normalization, and used the wrong chart. H100 normalization on the right should still stand.
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看好NBIS为行业龙头，静待市值超越CRWV。
@babyfolio 在我看来，它已经是明确的领导者！只等市场将 $NBIS 的未来增长/利润率计入定价，使其市值超越 $CRWV。
英文原文
@babyfolio It’s already the clear leader in my view! Just waiting for market to price in $NBIS forward growth/margins and the marketcap overtaking $CRWV.
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TPU虽具竞争力，但NVDA积压订单提供中期保障，难构成看跌。
是的，话题是关于TPU v7 Ironwood作为首个对$NVDA构成竞争替代的产品，在特定推理工作负载上表现更优。目前$NVDA的积压订单是中期的安全垫。关键问题在于TPU能否持续优于Nvidia旗舰GPU（我的答案是否定的，随着下一代发布）。然而，如果以下情况发生，则构成看跌逻辑：- TPU持续优于$NVDA旗舰GPU；- 人们更倾向于选择TPU而非NVDA芯片；- AI算力需求减弱，且$NVDA的GPU未完全售罄。
英文原文
Yeah, the topic was about how the TPU v7 Ironwood is the first competitive alternative to $NVDA and performs better for specific inference workloads. The current $NVDA backlog is a security guarantee for medium term. It's just a question of whether TPUs continue to outperform Nvidia's flagship GPUs (my answer is probably not, with the next gen release). It is a bear case, however, if - TPUs continues to outperform $NVDA flagship GPUs - people want TPUs over NVDA chips. - AI compute demand lessens, and $NVDA is not fully sold out of GPUs.
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对比GOOGL与NVDA，认为前者风险更低，后者潜在回报更高。
$GOOGL 具有非对称上行潜力。张量处理单元(TPU) 只是搜索、Waymo、YouTube 及其他业务之外的一个“支线任务”。 $NVDA 若 AI 随机器人/智能体指数级爆发，且其新模型在训练/推理性能上大幅超越其他供应商，则上行空间更大。 由于无法预知结果，同时持有两者无妨，但 Google 显然是两者中风险较低的选择。
英文原文
$GOOGL for asymmetrical upside. TPUs is just a side quest among search, Waymo, YouTube, and less other things. $NVDA for much higher upside in case AI continues taking off exponentially with robotics/agents and they end up leapfrogging all other providers in both trading/inference performance in their newer models. Doesn’t hurt to own both since it’s impossible to know, but Google is clearly the less risky of the two
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澄清NVDA与TPU性能对比误区，重申NVDA短期订单安全及长期技术优势。
是的，$NVDA 是强力买入标的。 然而，其他关于 $NVDA GPU 与 TPU 性能对比的病毒式传播的研究帖子，错误地拿旧一代 TPU v6e 来对比，以展示当前 $GOOGL TPU 与 $NVDA GPU 的情况。 我的帖子是关于新一代 TPU v7 Ironwood 与 $NVDA Blackwell B200 的对比，并展示了架构上的对等性。 TPU v7 Ironwood 的性能飞跃非常巨大（计算能力提升高达 10 倍），以至于 X 上流传的许多关于 TPU 推理能力和成本节约的研究具有误导性。 就买入逻辑而言，$NVDA 很可能在未来几代芯片中超越 TPU v7，且其巨大的积压订单为其提供了短期（2年）的安全性。
英文原文
Yes $NVDA is a strong buy. However to the other viral research posts about $NVDA GPU vs TPU performance, they were falsely comparing older generation TPU v6e to show the current situation on $GOOGL TPU vs $NVDA GPU. My post was on newer TPU v7 Ironwood vs $NVDA Blackwell B200 and showing the architectural parity. The TPU v7 Ironwood performance leap is so substantial (up to 10x compute jump) that a lot of research going around X is misleading on the inference capabilities and cost savings of TPU. In terms of buy thesis, on $NVDA, they will likely leapfrog TPU v7 in newer gen chips in due time and their immense backlog provides them near term (2Y) security.
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NVDA短期强烈买入，下一代芯片优势明显，市场未放缓。
哈哈，我之前在 $NVDA 的公关稿下当“神评论” trolling（嘲讽/玩梗）火了。所以想帮我的哥们 Jensen 一把，写写关于 TPU vs GPU 争论的看法，以及股价下跌是否反应过度。给快速浏览的朋友划重点： - 基于订单积压（Backlog）的可见性，短期强烈买入。 - $NVDA 下一代芯片很可能在技术上超越 TPU。 - AI 市场正在扩张，我们没有看到放缓迹象。 - 唯一需要担心的是，如果人们刻意去买 TPU/AMD，即下一代超大规模云服务商（Hyperscaler）芯片，那也只有在 $NVDA 生产的任何 GPU 都卖断货的情况下才会发生。
英文原文
lol I was top comment trolling $NVDA's press release that went viral. so wanted to do my buddy Jensen a solid by writing up thoughts on TPU vs GPU arguments + whether stock drop was an overreaction. So TLDR for people skimming the post: - strong buy near term from backlog visibility - nvda next-gen chips will likely leapfrog tpu - ai expanding market, we're not seeing it slow down. - only thing to worry about is if people go out of their way to buy TPUs/AMD, next gen hyperscaler chips if and only if NVDA stops selling out of any GPUs they make.
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英伟达虽面临谷歌TPU等定制芯片竞争，但中期统治力稳固，逢低买入。
英伟达($NVDA)公布的2026财年Q3营收为570.1亿美元(+62.5% YoY)，表现强劲。并指引Q4营收超650亿美元(超预期30亿美元+)，以及通过CY 2026年Blackwell/Rubin系列营收超5000亿美元。尽管如此，股价仍下跌12%。现在$NVDA是强力买入吗？答案如下： $GOOGL的TPU项目成为首个对$NVDA GPU构成竞争替代的方案，Anthropic承诺采购超100万颗TPU芯片，Meta据报道正在就数十亿美元的TPU采购进行高级别谈判。沃伦·巴菲特近期也向$GOOGL投资超40亿美元，鉴于伯克希尔对科技股保守的投资立场，这极为罕见。 尽管创下盈利新高，英伟达股价在过去10个交易日中有6天下跌，较10月29日触及5.03万亿美元市值时的历史高点$207.04下跌约12-15%。 分析师反应普遍看多，普遍上调目标价： - Evercore ISI从$261上调至$352 - 美银从$235上调至$275 - 花旗从$220上调至$270 - 高盛从$240上调至$250 - 摩根士丹利从$220上调至$235 但这里有个价值万亿美元的问题：超大规模客户日益增长的定制硅片威胁是否会削弱英伟达在AI领域的统治地位？ 与主要捕捉英伟达GPU缺货时的溢出需求的$AMD不同，谷歌的TPU项目代表了根本不同的竞争动态。 TPU v7 Ironwood是首款在性能上与Blackwell持平的非英伟达加速器，提供4.6 petaflops的FP8性能（对比B200的4.5 petaflops），配备192GB HBM3e内存。 Ironwood的架构差异化显著。虽然英伟达最大的集群配置为72个GPU(NVL72)，TPU Ironwood可扩展至9,216个芯片组。 客户斩获显著且不断增长： - Anthropic承诺采购超100万颗TPU芯片，价值“数百亿美元”，1GW算力即将上线。 - Meta正在就2026年从谷歌云租赁TPU容量进行高级别谈判，并计划2027年直接采购硬件用于自有数据中心。 - 苹果透露Apple Intelligence基础模型完全在TPU上训练，使用8,192颗TPUv4芯片用于服务器模型。 - Midjourney从GPU转向TPU，推理成本降低65%（从每月200万美元降至70万美元）。 定位微妙。TPU在超大规模推理方面表现出色，在生产级大规模服务中成本性能最高提升4倍（目前）。在训练方面，英伟达优势明显。 对于高度优化的推理任务，TPU架构可能比$NVDA的通用GPU更高效。 然而，我预计下一代英伟达GPU将在许多场景下在推理性能上超越TPU。（类似于LLM之间GPT 5 -> Gemini 3 -> Opus 4.5的迭代超越） 我们看到： 谷歌TPU、AWS Trainium、Meta MTIA、微软Maia和定制超大规模芯片都在扩展，但仍依赖$NVDA。但超大规模客户集体减少对英伟达的依赖，其累积效应是否会削弱英伟达的统治地位？ 答案：不会。至少未来两年统治地位稳固。之后如何纯属猜测。 仅看数据：Q3结果证实公司仍是AI不可或缺的基础设施提供商，5000亿美元的订单积压为2026年提供了极高的可见性。 但市场似乎正在定价3年+后的这种微妙现实：长期面临超大规模客户定制芯片的竞争不确定性。 英伟达产能完全售罄，且很可能在下一代芯片中超越TPU性能（推理性能更高且保持通用性）。但定制硅片威胁和44倍市盈率的估值担忧仍是逆风。 无论如何，鉴于出色的超预期财报和未来两年的订单积压，$NVDA目前因恐惧而下跌，似乎是中期强力逢低买入的机会。 你只需要记住这一点： 只要英伟达仍是AI工作负载的行业首选，且TPU和AMD GPU仅在需求超过英伟达供应时填补空白，它就是强力买入标的。 英伟达订单积压已满，AI需求并未放缓。
英文原文
Nvidia ( $NVDA ) reported a blowout Q3 FY2026 revenue of $57.01 billion (+62.5% YoY). And guided $65B+ Q4 ($3B+ beat), and $500B+ USD in Blackwell/Rubin rev through CY 2026. Despite that, the stock dropped 12%. Is $NVDA a strong buy now? Here's the answer: $GOOGL TPU's program emerged as the first competitive alternative to $NVDA GPUs, with Anthropic committing to over 1 million TPU chips and Meta reportedly in advanced negotiations for billions in TPU purchases. Warren Buffet also recently invested $4B+ into $GOOGL, which is extraordinarily rare given Berkshire's conservative stance to tech investments. Despite a record earnings beat, Nvidia's stock has declined in six of the last ten trading sessions and sits roughly 12-15% below its October 29 all-time high of $207.04, when it briefly touched a $5.03 trillion market cap. Analyst reaction was overwhelmingly bullish, with price targets raised across the board: - Evercore ISI raised to $352 from $261 - Bank of America raised to $275 from $235 - Citigroup raised to $270 from $220 - Goldman Sachs raised to $250 from $240 - Morgan Stanley raised to $235 from $220 But here's the trillion dollar question: will the emerging custom silicon threat from hyperscalers reduce NVIDIA dominance in AI? Unlike $AMD, which primarily captures overflow demand when NVIDIA GPUs are unavailable, Google's TPU program represents a fundamentally different competitive dynamic. TPU v7 Ironwood is the first non-NVIDIA accelerator that achieves performance parity with Blackwell, delivering 4.6 petaflops of FP8 performance (versus B200's 4.5 petaflops) with 192GB HBM3e memory. Ironwood's architectural differentiation is substantial. While NVIDIA's largest cluster configuration is 72 GPUs (NVL72), TPU Ironwood scleaes to 9,216 chip pods. The customer wins are significant and growing: - Anthropic committed to over 1 million TPU chips worth "tens of billions of dollars," with 1 gw of compute capacity coming online. - Meta is in advanced negotiations to rent TPU capacity from Google Cloud in 2026, with direct hardware purchases for its own data centers planned for 2027. - Apple revealed that Apple Intelligence foundation models were trained entirely on TPUs using 8,192 TPUv4 chips for server models - Midjourney switched from GPUs to TPUs and reduced inference costs by 65% (from $2M to $700K monthly) The positioning is nuanced. TPUs excel at hyperscale inference with up to 4x better cost-performance for production serving at scale (for now). For training, NVIDIA is the clear advantage. For highly optimized inference tasks, TPU architecture might remain more efficient than $NVDA's general-purpose GPU. However, I'm expecting next-gen Nvidia GPUs to leapfrog TPUs for inference in many scenarios. (similar to how LLMs leapfrog each other GPT 5 -> Gemini 3 -> Opus 4.5) We're seeing: Google TPU, AWS Trainium, Meta MTIA, Microsoft Maia, and custom hyperscaler chips scale up to reliance on $NVDA. But will the cumulative effect on hyperscalers collectively reducing Nvidia's dominance? The answer: No. Not yet. Dominance is secured at least for the next two years. What happens after is only speculation. Just looking at the numbers: Q3 results confirm the company remains the essential infrastructure provider for AI, with a $500 billion order backlog providing exceptional visibility through 2026. But the market appears to be pricing in this nuanced reality 3 years+ from now: long-term competitive uncertainty with custom hyperscaler chips. Nvidia is completely sold out of capacity, and are likely to leapfrog TPU performance in their next generation chips (higher performance for inference while being general purpose). But the custom silicon threat and valuation concerns at 44x earnings remains a headwind. Regardless, $NVDA seems to be a strong mid term dip-buy now on fears, given the exceptional blowout earnings and backlog for the next 2 years. This is the only thing you need to remember: NVIDIA is a strong buy as long as it remains the industry’s first choice for AI workloads, with TPUs and AMD GPUs filling gaps when demand exceeds NVIDIA’s supply. Nvidia is maxed out on backlog, and AI demand is not slowing down.