Anthropic

$Meta Platforms(META.US)

BREAKING: Meta is in talks to rent computing capacity to Anthropic in a deal worth up to $10B over 2 years, as per the New York Times.

Meta went down today on news that they hired a senior AWS executive to help build their cloud division.

Why? Because it was confirmation that they are doubling down on capex and selling compute, which means their FCF will take a hit. Ironically, the semis should have been up on this news but the Kimi K3 headlines have kept them down.

Now, Meta is slightly reversing on this headline about selling compute to Anthropic…which begs the question…if the market is happy about Meta selling compute to a big lab, why are they upset about Meta spending more on capex in order to build that compute business?

Tons of weird narratives conflicting with each other, but it looks like META is officially getting into the neocloud game.

Source: amit

Meta $Meta Platforms(META.US) may lease computing power to Anthropic in a deal worth ~$10 billion.

Anthropic reportedly proposed the deal in June, and Meta is "considering it", per NYT.

The deadliest mountain in the world is K2 in Pakistan.

But how deadly will the new K3 model by Moonshot be?

In my view, this is not another "DeepSeek" moment. Kimi K3 is net-positive for the AI trade and compute demand, while being a net-negative for Western fronteir labs.

After reading many reviews on X, my understanding is that Moonshot are just a few months behind the fronteir, rather than a full generation behind.

I will caveat that I am far from being an AI "expert". However, I believe I understand the commercials at a high enough level to comment on and summarize.

So from a commercial point of view, K3 comes out at roughly half the cost of Opus 4.8 for a slightly better model overall. Moonshot is charging ~$3 per million input tokens and ~$15 per million output tokens, the same rate card as Anthropic's mid-tier Sonnet and nearly 4x its own previous model.

In my opinion, these pricing dynamics are what makes the DeepSeek comparisons I've seen on X to be very lazy.

DeepSeek in Jan 2025 was a deflation event where they had near frontier capability built very cheaply and effectively given away at such low prices which implied that Western AI capex was excessive.

Moonshot is doing the opposite. It's charging Western prices because it believes it is selling capability, not cheapness, most likely because Chinese labs are starving for compute and actually need the revenue to continue building and serving demand.

The business model for fronteir labs like OpenAI and Anthropic is essentially the monetisation gap between their own leading models and everyone elses. Both of those companies are raising money at valuations that assume that gap stays wide and highly monetisable for years to come (at growing rates).

However, many AI experts on X say that the Kimi K3 gap can now be measured in months, and that the tier just below the frontier, where the bulk of real commercial workloads actually run, is potentially about to be served up at very low commodity prices.

As a result, the labs' defensible ground shrinks to the true frontier, to enterprise trust and security, and to distribution. Revenue can keep growing while pricing power erodes, and in my view, it is the pricing assumption (not the demand assumption) that carries Anthropic's and OpenAI's lofty valuations.

Using SoftBank as a proxy for OpenAI, we saw today that their stock price fell a huge 9% after Kimi K3 was released. I believe, now, that this valuation-digest was and is warranted.

I know many of my followers will care about the AI trade in upstream names though. However, I do not view the latest Kimi K3 model as having a fundamentally negative impact on those companies.

Every K3 token will still consume chips, memory and power that remain effectively sold out into next year. Moonshot will certainly need to secure additional compute to facilitate growing demand for their models.

As of right now, it does seem like exposure to model-layer margins, lab valuations and their listed proxies looks worse.

Conversely, exposure to the infra in upstream supply chain names that serves tokens regardless of whose model wins looks cheaper, all things considered, for no fundamental reason.

However....to be slightly more contrarian - you could argue that if cheaper Chinese models come to market at a rate of knots and leads to margin compression for the likes of OpenAI and Anthropic ---> will that not have a negative effect on their spend in the long-term? As a result, a negative effect on the upstream AI supply chain?

I am yet to think through this in much detail, but it certainly deserves exploring.

I want to finally mention some of the technical experts I have enjoyed reading since Kimi K3 came out, as a non-technical person:

- @zephyr_z9

- @scaling01

- @FundaAI

If you want to be someone who is constantly learning about AI, these guys are must-follows in my opinion.

Of course, as always, I would encourage anyone to correct me or debate me if I am wrong in any area.

Ashton Kutcher made $1.2B more from his OpenAI bet than 25 years of acting

He co-founded a firm with Guy Oseary in 2015 called Sound Ventures

Sound Ventures' history:

• Invested when OpenAI was worth $20-29B

• Now worth $850B+

• 43x return in under 3 years

• Also early in Anthropic, Brex, and Gusto

He made $90M acting over 25 years, yet one fund's bet outperformed decades of work

Still, he recently left Sound Ventures to start Decimal Capital with Morgan Beller. Their focus is early-stage semiconductors, nuclear, robotics, biotech, and energy companies

📢 𝐉𝐔𝐒𝐓 𝐈𝐍: Anthropic, Blackstone, and Hellman & Friedman Launch Enterprise AI Firm Ode

👉 𝐊𝐞𝐲 𝐇𝐢𝐠𝐡𝐥𝐢𝐠𝐡𝐭𝐬:

➤ 𝐀𝐧𝐭𝐡𝐫𝐨𝐩𝐢𝐜, 𝐁𝐥𝐚𝐜𝐤𝐬𝐭𝐨𝐧𝐞, and 𝐇𝐞𝐥𝐥𝐦𝐚𝐧 & 𝐅𝐫𝐢𝐞𝐝𝐦𝐚𝐧 launch 𝐎𝐝𝐞.

➤ Ode is a standalone 𝐞𝐧𝐭𝐞𝐫𝐩𝐫𝐢𝐬𝐞 𝐀𝐈 services company.

➤ Ode is built on 𝐅𝐫𝐚𝐜𝐭𝐢𝐨𝐧𝐚𝐥 𝐀𝐈, acquired in May 2026.

➤ 𝐂𝐡𝐫𝐢𝐬 𝐓𝐚𝐲𝐥𝐨𝐫 becomes CEO and 𝐄𝐝𝐝𝐢𝐞 𝐒𝐢𝐞𝐠𝐞𝐥 serves as CTO.

➤ Backers include 𝐆𝐨𝐥𝐝𝐦𝐚𝐧 𝐒𝐚𝐜𝐡𝐬, 𝐆𝐞𝐧𝐞𝐫𝐚𝐥 𝐀𝐭𝐥𝐚𝐧𝐭𝐢𝐜, 𝐀𝐩𝐨𝐥𝐥𝐨, 𝐆𝐈𝐂, and 𝐒𝐞𝐪𝐮𝐨𝐢𝐚.

➤ Ode combines 𝐀𝐧𝐭𝐡𝐫𝐨𝐩𝐢𝐜'𝐬 AI models with applied AI engineering expertise.

➤ Company targets 𝐟𝐢𝐧𝐚𝐧𝐜𝐢𝐚𝐥 𝐬𝐞𝐫𝐯𝐢𝐜𝐞𝐬, healthcare, retail, manufacturing, and software.

➤ Ode focuses on helping enterprises deploy 𝐀𝐈 into core business operations.

➤ Company is actively hiring 𝐞𝐧𝐠𝐢𝐧𝐞𝐞𝐫𝐬, product leaders, and operators.

👉 𝐄𝐱𝐩𝐞𝐫𝐭 𝐒𝐭𝐚𝐭𝐞𝐦𝐞𝐧𝐭𝐬:

𝐂𝐡𝐫𝐢𝐬 𝐓𝐚𝐲𝐥𝐨𝐫, CEO of Ode:

"Companies everywhere see the potential for what AI can do for their businesses, the challenge is making it real. By pairing the deep subject matter expertise of our clients with our top applied AI talent, we're able to drive transformation level impact."

𝐆𝐚𝐫𝐯𝐚𝐧 𝐃𝐨𝐲𝐥𝐞, Head of Forward Deployed Engineering for the Americas at Anthropic:

"Ode was built to be that partner, adding to Anthropic's growing ecosystem of partners that help enterprises put Claude to work."

Man...these token costs are starting to seriously become an issue.

Yes, companies want to generate as many useful tokens as possible, but they really don't want to pay for them if open-source alternatives exist.

Anthropic and OpenAI are starting to realize the reality of this and have started to give out as much free compute as they can in order to lock startups into using their models over others, as per the WSJ.

This is probably a necessary thing to do for these model companies and they have capital to subsidize giving away the compute, but it also speaks to how serious the wars for tokens are becoming.

As both OpenAI and Anthropic get ready to go public, they need more levers for growth and it feels like rev-sharing with many of the companies they work with, or some version of sharing in the upside in exchange for compute, may be part of the way they lock people into their models so that they don't go the cheaper route for tokens.

Or, they try to drive token costs down further and find their margin in different areas, but more and more companies are questioning how much they should be paying for tokens.

Source: amit