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所有人都在买英伟达，没人注意到这根连接所有AI芯片的管道——Nokia 上一篇写了为什么nokia是最便宜的光，今天再来详细分析一下4月份的财报和未来方向。有没有可能重现1999-2000年的parabolic move? 一、先说一个被忽视的逻辑 AI投资的讨论永远围绕着芯片——谁的GPU更快、谁的HBM供货更足。但没人问一个更基础的问题这些GPU之间，用什么连接？ 数据中心里成千上万颗GPU需要实时互相通信，传输的数据量是普通网络的数百倍。现有的网络基础设施正在被这股流量压垮。打通这个瓶颈，就是下一个十亿美元级别的机会。Nokia就站在这个瓶颈的收费站口。 二、4月份财报说了什么 表面数据：Q1净营收45亿欧元，整体年增率4%。很多人看到这个数字转头就走。 但分开来看： 1. AI与云端客户营收年增49% 2. 光通讯业务单季成长20% 3. 营业利益率冲上6.2%，年增200个基点 4. 自由现金流单季6.29亿欧元 5. EPS大超分析师预期31% 6. 净现金储备近40亿欧元 7. 已启动股票回购 更关键的是，管理层把光通讯与网络互联业务全年指引从10-12%直接上修到18-20%。大型设备商几乎从不这么做——除非手头的订单已经多到藏不住。10亿欧元实质采购订单，带明确交付日期，不是框架协议。客户之所以愿意压上日期，说明数据中心土建已完成，服务器准备进场，就等Nokia的设备到货。 三、为什么是Nokia，不是别人 重点一：与英伟达深度绑定 Nokia与英伟达达成AI-RAN战略合作，把GPU算力直接整合进无线电网络。年底还有双方合作的光电共封（LPO）现场试验数据即将公布。 黄仁勋说Agentic AI带来1000%的算力需求暴增。这1000%的算力要运转，需要1000%更宽的传输通道。Nokia在造这个通道，英伟达需要这个通道。 两家公司的利益高度一致。 重点二：Infinera并购协同效应超预期 高利率环境下，Nokia凭借近40亿欧元净现金逆势完成对Infinera的收购，并购带来的毛利率提升速度远超华尔街预期。这笔并购很完美，营收规模越大，利润爆发力越强。 重点三：主动放弃低毛利，聚焦Webscale巨头 Nokia正在主动削减消费者光纤等低毛利业务（固网业务Q1下滑13%），把所有产能死死锁定在谷歌、亚马逊这类超大型云端数据中心客户。 表面营收看起来疲软，实际是在牺牲数量，保住利润率。这种"价值重于数量"的策略，在产业周期里往往是股价主升段的前兆。 订单出货比持续大于1，接单速度快过交货速度，积压需求将在未来几季持续转化为营收。 四、市场有多大 云端巨头2026年资本支出超过7250亿美元，整个潜在市场年复合成长率从16%跳升至27%。目前AI驱动的网络流量只占整体的20%。随着Agentic AI和Physical AI的普及，机器对机器的数据传输将呈指数级增长——现有网络根本撑不住。Nokia不需要抢市场，只需要站在这条必经之路上收过路费。 五、风险在哪 供应链瓶颈： 光通讯产品交期被拉长至12-18个月，上游数字信号处理器（DSP）大缺货，营收认列速度被掐住。订单很多，但转化成钱需要时间。 无定价权： Nokia的增长靠的是出货量，不是涨价。光通讯产品长期价格向下，利润扩张依赖规模经济，这是苦活不是躺赢。 新交换器业务存在转换空窗期： Q1拿到的设计导入（Design Wins）不会立即贡献营收，需要等Q2-Q3的订单转化。 2027年新架构才放量： 下一代光电共封架构能降低客户总置成本70%，但量产要等2027年下半年，别把2027年的故事算进2026年的EPS。 六、会不会重现1999-2000年的parabolic move行情？ 1999年Nokia是全球最大手机厂，市值一度超过2000亿美元，两年内股价涨了超过10倍。那次是5G前身的2G/3G爆发周期。 这次不同，也更扎实。那次靠的是终端设备消费，周期性极强。这次靠的是基础设施刚性需求，数据中心建好就要配套设备，不存在等等看再说。 抛物线行情需要三个条件： 1. 需求端爆发: 7250亿资本支出，明年资本开支持续增加，AI流量暴增 2. 供给端瓶颈: 交期12-18个月，产能跑不赢订单 3. 市场认知滞后: 大部分人还把Nokia当5G周期股在看 认知差就是超额收益的来源。当市场还在争论Nokia是不是无聊的电信设备商，机构资金已经在悄悄重新定价。 七、三个必须持续跟踪的数据 1. Q2开始看设计导入转化率: Q1拿到的客户认证，有没有在Q2变成真实采购单，这决定下半年营收基础 2. 光通讯交期有没有开始收缩: 从18个月降到12个月是一个信号，意味着上游供应链开始松动，营收加速的拐点就在附近 3. 年底LPO试验数据: 与英伟达合作的光电共封现场测试，一旦数据亮眼，Nokia的估值逻辑将从"电信设备商"切换到"AI基础设施核心供应商"，PE重估空间巨大 八、总结 这不一定会是1999年的抛物线，但认知差带来的重估行情，逻辑上已经非常清晰。等年底英伟达LPO试验数据出来，才是真正的验证时刻。 #NOK# #Nokia# #NVDA# #AIInfrastructure# #OpticalNetworking# #Datacenter# #AI超级周期# #光通信#

ZERO ALPHA Research Preview | Reframing NVDA NVIDIA’s latest earnings report is the trigger event for a new round of deep research. A company already among the largest in the world just delivered 106% year-over-year revenue growth, with Data Center revenue up 117%. What is striking is not simply that NVIDIA beat expectations again, but that its core business has returned to a doubling growth rate from an already enormous base, even as AMD GPUs, hyperscaler-designed chips, and custom AI accelerators continue to enter the market. That prompted us to go back and re-examine NVIDIA’s full growth trajectory since 2023. When revenue growth, earnings growth, stock-price appreciation, and P/E are viewed together, a very different pattern begins to emerge. The first NVIDIA spring was largely top-down. The market recognized the potential of generative AI first, the stock price moved ahead, and earnings later caught up. The second spring now looks increasingly bottom-up. Revenue growth re-accelerated from: 56% → 62% → 73% → 85% → 106% while valuation multiples moved lower rather than higher. In simple terms: First Spring: P led E. Second Spring: E is beginning to lead P. This earnings report therefore may represent more than another earnings beat. It may be a signal that NVDA itself needs to be reframed. It also raises a broader question: What actually defines a true mega-cap growth stock? A high P/E alone does not define growth. The rarest structure may be a company that is already enormous, still grows its core business near 100%, generates earnings faster than its stock price rises, avoids excessive valuation expansion, and continues to create new TAM. Applying this framework to AMD, MU, SNDK, LITE, ALAB, DELL, and the hyperscalers makes the leadership hierarchy increasingly clear. Many of them have strong growth, but each still carries a weakness in valuation, cyclicality, pricing dependence, platform control, or growth durability. NVDA currently presents a more unusual combination. More importantly, at least four additional growth engines are still developing: Pricing Power Supply Efficiency Open Models Inference Specialization If these continue to develop, today’s NVIDIA may not yet represent the peak of this second growth cycle. And NVIDIA’s second spring may not belong to NVIDIA alone. Memory and storage, optical networking, and AI data-center operators could all benefit if another AI infrastructure expansion cycle is now beginning. ZERO ALPHA will therefore use this earnings report — a mega-cap company returning to 100%+ core growth — as the starting point for a six-part NVDA Research Note series: 1/6. NVDA: The Second Spring — From P Leading E to E Leading P 2/6. NVDA: What Defines a True Mega-Cap Growth Stock? 3/6. NVDA: Why It Is Still in Its Prime, Not Near the Peak 4/6. NVDA: Four New Growth Engines — How Far Can the Second Spring Go? 5/6. NVDA: Why Leaders Lose Leadership — Lessons from Intel, Tesla, and AMD 6/6. NVDA: Will the Second Spring Reignite the Entire AI Infrastructure Chain? Each note will focus on one independent question and can be read on its own. ZERO Insight The most important message from this earnings report may not be that NVIDIA beat expectations again. It may be this: When a company already this large returns to 100%+ core growth while trading at a much lower P/E than during its first AI explosion, what needs to be revalued may not be just NVDA’s stock price — but our entire understanding of mega-cap growth.