Key Updates: 🔹 AI Cloud Contracts: More than $30B booked in Q1, increasing RPO to $664B 🔹 ATM Equity Program: $20B of common stock sold before commissions
$NBIS Continues to look good here, this stock is the sector leader when it comes to neoclouds and should lead others higher as it pushes to +$400 a share
It wont be a straight line to $400, there will be dips along the way just like today, but the trend is pointing to $400 a…
Just some notes from NBIS fireside chat at Goldman Sachs Tech Conference:
TLDR: Yep, it's bullish. 1. Order book extends into H1 2028 which is 2 quarters further out than at Q2 ER. Arkady said "people are demanding tens of thousands of vGPUs and GPUs now. So we see demand today as unlimited." Bro...what?!! At Q2, they said that all of 2027 could be sold today. But Nebius having visibility ~1.5 years away massively de-risks their ~5GW contracted power target and their ~$25B of FY26 capex. On demand, Arkady also said that demand visibility now extends to 24+ months (vs. 18 months previously). This is HUGE because demand duration is a huge crux for neocloud bears (kinda makes sense why). Even CRWV CEO said at the GS Conference that they are "struggling to meet demand everyday." 2. "We do not pre-sell much. We are focusing on free capacity, which we will be selling later I think two things are happening here with Nebius First - this is the opposite of $CRWV 's model where their ~$104B backlog is take/pay dynamics. Nebius are instead choosing to sit on uncontracted 2027 capacity so they can sell into rising prices, kinda like how $MU and co. were doing pre-LTAs. Second - keeping some spare capacity keeps room for longer-term strategic partners arriving into 2027 (which will be extremely supply-constrained). I.e. enterprise names coming via the $PLTR partnership. I think both reasons make sense, I'm fairly confident that 2027 pricing will be higher. 3. "We actually have a list of new customers that are looking for any of the older generation chips that come available." This lines up with CRWV disclosing at Q2 an A100 contract priced out to 2029 and completely guts the residual-value thesis bears like Burry lean on. 4. $SHOP "used open-weight models, trained it with their own data repetitively, and they achieved the quality which is higher than they had with GPT-5 and 6." Feels like that's the whole enterprise adoption thesis summarized....narrow domain, pvt data, repeated loop, open weights > fronteir, at a fraction of the cost. Probably also why the token factor and the Tavily acq. matter. So yeah, Nebius' entire infrastructure goes kinda crazy. More than just GPU rental. 5. Contract mix Marc: 3-6 month short-term deals go out "at a multiple of the ARR per megawatt" of the core. 1-3 year medium-term deals are "the lion's share" and 5+ year hyperscaler deals were done "with the explicit intent that we are looking for the capitalization benefit." - So the longer duration $MSFT + $META contracts are lower risk collateral for financing the build - the opportunistic short-duration surge contracts at materially higher pricing are the top-ups. - and the 1-3 year book with AI natives and enterprises (priced above hyperscaler deals + prepaid) are the core + fastest growing segment. Just for a summary of the points I found most interesting / different from Q2 earnings. Cool to also see the "the vision that Arkady has is us becoming a hyperscaler." I've been sharing the same vision for some time now, and is why Nebius ultimately deserve to trade multiples higher than Coreweave for example.
Palantir $PLTR and Nvidia $NVDA just announced a new partnership to "bring sovereign AI to critical supply chains, starting with NVIDIA’s own operations."
The two companies built an AI stack combining NVIDIA's open Nemotron models with Palantir's Foundry, AIP, and Ontology, aimed at giving NVIDIA's supply chain teams real-time visibility into constraints and faster materials allocation decisions across a network of millions of parts and thousands of suppliers
HUAWEI HIKES TOP AI CHIP PRICE 60% AS DEMAND OUTSTRIPS SUPPLY
Huawei has raised the suggested price of its Ascend 950DT to about 250,000 yuan, or $37,300, over the past three months, putting it roughly in line with NVIDIA’s $NVDA B200.
The increase comes as demand for Chinese AI compute surges. DeepSeek plans to deploy at least 160,000 Ascend 950DT chips in a major Inner Mongolia data center.
Supply remains constrained by limited HBM availability, pushing up costs and forcing Huawei to prioritize larger customers.
Cambricon is also reportedly raising AI chip prices by as much as 30%.
JPMORGAN UPGRADES $META TO OVERWEIGHT, RAISES PT TO $820 FROM $640
JPM sees Meta’s AI upside moving well beyond ads, with Muse, Model API and Business Agents opening new revenue streams, while its ~4B-user distribution gives it a major scaling advantage.
It also sees further upside to Meta’s core ad business from AI-driven recommendations, engagement and better targeting.
JPM expects the upcoming Watermelon model to be another meaningful step up in intelligence and capabilities, with post-Watermelon models already scaling on Meta’s Prometheus cluster in Ohio.
Stock recently broke out of a 3 week consolidation from sitting at the 50 EMA and it is now making lower highs, also the daily BX has turned green which means buyers are ready to push it higher.
The relative strength in this sector can't be ignored either, the market has been pushing the memory trade higher while oil keeps making new highs.
Stock is above all major 9/21/50 weekly EMA's, BX is flipping to lighter red about to turn green last two times this happened stock ran up 250%+, stock has been compressing for months just waiting to explode
Some catalysts could be INSANE 2027 ARR guidance or management landing another deal which are both very possible
$VICR.US held a world record in 2017 for the exact architecture the entire AI industry is racing toward now. Then the story disappeared.
Here's the setup. Power loss scales with the square of current, not power. Double the current, you burn four times the energy. That's just what copper does, no amount of capital fixes it.
A wafer-scale AI processor pulling 20 kilowatts at 0.6 volts needs 33,333 amps. More current than a lightning bolt, continuously, into a chip the size of a dinner plate.
Deliver that at 6 volts and you lose 2,200 watts getting it there, 11% of the entire power budget turned into heat. Deliver it at 48 volts and you lose 35 watts. Same chip, same power, one decision about voltage, 64 times the difference.
There are two ways to step voltage down that far. A switch flipping on and off fast, which is what almost everyone ships, Monolithic Power, Infineon, Analog Devices, TI. Or a transformer that trades volts for amps at a fixed ratio, the way a gearbox trades speed for torque.
Vicor is one of the only companies doing it the second way, and they've been building this architecture since the early 1980s.
Now the world record. In November 2017, a Vicor-powered supercomputer called Gyoukou held the record for computing efficiency using this exact setup, co-packaged power conversion, direct 48V to sub-1V at the chip.
That's the entire 2026 AI power pitch, and it was in production and world-record-holding nine years ago. customer's CEO got arrested 19 days later on an unrelated fraud charge and the whole program died with him. It's vanished from every current research note on this company.
There's also a licensing business here running near 100% margin. They don't sue customers, they go to the ITC and get customs to block the infringing supplier at the border. One deal closed in three weeks for $60 million because a hyperscaler's supplier got physically stopped at the port.
Proven technology, a world record to back it up, and a licensing weapon that gets paid regardless of who wins the sockets. Question is whether they can finally convert it.
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