DeepSeek

I've mapped the entire Wall Street bear playbook on AI names:

Have your favorite institution/media insert one of these name down below:

1. < ______ [GPUs, Transcivers, MLCC, Memory...] are a commodity set to crash>

2. < ______ [YMTC, CXMT, Dongshan...] from China will flood the market >

3. < ______ [Micron, Nvidia, ...] from unverifiable channel checks is facing issues >

4. < ______ [Kospi, Sivers, ...] is a bubble like the ____ [2007, 2021] crash>

5. <____ [1,2,3, ...] unexpected rate hikes this year>

6. < _____ [Google, Nvidia, Deepseek ...] optimization removes the need of this!>

in a new headline, and it's ready to go!

$NVIDIA(NVDA.US)

NVIDIA'S JENSEN HUANG GIVES AN UPDATE ON KIMI K3 AND CHINA'S OPEN SOURCE MODELS:

"American companies should absolutely be allowed to use Chinese AI models. There's a misconception that somehow there are backdoors connected to China in someway. You download the models, fine tune them, guardrail them in any way you want."

"These Chinese opensource models are excellent. The market has misunderstood the impact of DeepSeek the first time. It's misunderstood the impact of Kimi this time. Open models are great for the whole industry, there will be more usage which will require selling more Nvidia computers and building more datacenters."

"Great models lead to more usage. There is also a misunderstanding that open models are going to hurt the closed models, that is also wrong."

Source: amit

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.

📢 𝐉𝐔𝐒𝐓 𝐈𝐍: DeepSeek Begins IPO Preparations, Eyes 2027 Public Debut

👉 𝐊𝐞𝐲 𝐇𝐢𝐠𝐡𝐥𝐢𝐠𝐡𝐭𝐬:

➤ 𝐃𝐞𝐞𝐩𝐒𝐞𝐞𝐤 has begun preparations for an 𝐈𝐏𝐎, according to Bloomberg.

➤ Company is targeting a 𝐦𝐚𝐢𝐧𝐥𝐚𝐧𝐝 𝐂𝐡𝐢𝐧𝐚 IPO filing in 2026.

➤ Public market debut is planned for 𝐭𝐰𝐞𝐧𝐭𝐲-𝐭𝐰𝐞𝐧𝐭𝐲-𝐬𝐞𝐯𝐞𝐧.

➤ DeepSeek is working with 𝐚𝐜𝐜𝐨𝐮𝐧𝐭𝐢𝐧𝐠 and banking advisors.

➤ Company is seeking at least 𝐂𝐍𝐘 𝟏𝟎 𝐛𝐢𝐥𝐥𝐢𝐨𝐧 in new private funding.

➤ New funding targets a 𝐩𝐫𝐞-𝐦𝐨𝐧𝐞𝐲 𝐯𝐚𝐥𝐮𝐚𝐭𝐢𝐨𝐧 of at least 𝐂𝐍𝐘 𝟒𝟖𝟎 𝐛𝐢𝐥𝐥𝐢𝐨𝐧.

➤ Target valuation equals approximately 𝐒𝟕𝟏 𝐛𝐢𝐥𝐥𝐢𝐨𝐧.

➤ DeepSeek closed a record 𝐒𝟕 𝐛𝐢𝐥𝐥𝐢𝐨𝐧 financing round weeks earlier.

➤ IPO timing and fundraising plans remain 𝐬𝐮𝐛𝐣𝐞𝐜𝐭 𝐭𝐨 𝐜𝐡𝐚𝐧𝐠𝐞 based on conditions.

$Alphabet(GOOGL.US) is not just an AI model trade.

It is a cash-flow machine with Search, YouTube, Cloud, Android, Workspace, Gemini, TPUs, and Waymo all stacked together.

The bull case is simple:

Google can make AI cheap, useful, deeply embedded, and massively distributed.

That is why $Alphabet(GOOGL.US) may be one of the cleanest mega-cap AI value trades on the board.

Main risks to watch: antitrust remedies, heavy AI capex, and margin pressure if AI infrastructure costs rise faster than monetization.

$Alphabet(GOOGL.US) $Alphabet - C(GOOG.US)

Gemini 3.5 Flash at $9 per million output tokens is the standout value layer here.

That is roughly:

70% cheaper than OpenAI

64% cheaper than Claude Opus

82% cheaper than Claude Fable

DeepSeek wins raw low-cost pricing.

But Google brings the full machine:

@WarrenPies