GYST

Born to cook and go hard

[GYST @gystmofos]

@SteveUrkelDude Real og’s Remeber Trevor Milton and the freewheeling truck

[GYST @gystmofos]

@smartertrader

[Gavin Baker @GavinSBaker]

Kimi K3 may be an important inflection point for AI. Potentially negative for Anthropic and OpenAI while being net positive for essentially every other company in the world. I mean that very literally. Although the real “Sputnik moment” would be an open-source frontier model that was also token efficient unlike Kimi K3 which is 50-70% more expensive to run than GPT 5.6 per Artificial Analysis.

Rationale:

A world where there are only 2-3 dominant frontier labs with 90% inference margins is net negative for every other layer while being awesome for those 2-3 labs. Those labs would become monopsonies for power, data centers, semiconductors and hyperscalers and would obviously vertically integrate over time into all those layers while also completely subsuming the application/software layers. 

Anything that lowers margins and increases competition at the model layer is good for every other AI layer: power, semiconductors, hyperscalers, neoclouds and yes even software.

This is why Jensen is so supportive of open-source. An open-source model requires the *exact* same amount of compute to run as a closed frontier model of similar size and architecture. Kimi K3 is roughly the same price as GPT 5.6 Terra on a per token basis, which actually suggests that it is less computationally efficient as I am sure that GPT 5.6 is priced to a higher margin than K3. And given that K3 is a token wastrel, i.e. token inefficient, it is significantly more expensive per task than GPT 5.6 and Grok 4.5, which are much more token efficient. Cost per token and token efficiency (i.e. intelligence density per token) are the drivers of intelligence per unit of cost. The winning AI companies will be those that offer the most intelligence per $ over time.

Lower margin % at the model layer = more margin $ at every part of the infrastructure layer and is a godsend for software. This can happen either through open-source models like K3 at the frontier *or* having a vertically integrated model company like Meta, SpaceX or Google at the frontier. Both outcomes result in a lower margin % at the model layer as vertically integrated model companies don’t really care where the margin $ come from. This is why it was so painful for OpenAI and Anthropic when Google was right there with them from a model competitiveness perspective and why Grok 4.5 and Muse 1.1 were just as important as Kimi K3.

The reason Kimi K3 is only *potentially* negative for Anthropic and OpenAI is 1) the @ericvishria point that the Claude and ChatGPT products and harnesses may be more important than their models today and 2) the hypothesis that they have much more advanced model checkpoints internally that are already being used for RSI. In the latter scenario, reaching RSI even a few months ahead of other labs might be enough to cement a permanent lead.

Time will tell on both points. And likely fairly quickly.

Caveat would be that since Kimi K3 is not token efficient and thereby actually more expensive than ChatGPT 5.6, we may need to see a more token efficient open-source model at the frontier or see Grok 5/Composer 4/Muse 2 at multiple points on the Pareto frontier for this potential risk to Anthropic and OpenAI to play out. And I am sure they will both vertically integrate as quickly as possible while continuing the product/harness strength they have shown over the last 8 months.

[GYST @gystmofos]

@NickRTFM When you have a leveraged buyout, the new owners gotta justify payback for the purchase = more revue raise/creep….ain’t nothing gonna change sadly

[Paul Embery @PaulEmbery]

A brilliantly accurate dissection of England’s self-destruction. Every word is spot on.

[Semiconductor Insider @SemiconductorsX]

DRAM prices are surging 20-30% in Q3 2026 as AI demand starves consumer supply.

Samsung is pushing aggressive hikes. LPDDR is even higher.

SanDisk $SNDK just locked multi-year LTAs with Meta for flash storage. Micron $MU has 16+ such agreements.

These are signed commitments with floor pricing that de-risk earnings.

Meanwhile, 800G transceiver demand keeps revising upward. Lasers are sold out into early 2029. Photonics and optical components are critical for scaling data centers.

Yet those stocks get sold off too.

[GYST @gystmofos]

@FabrizioRomano

[GYST @gystmofos]

@NickRTFM

[GYST @gystmofos]

@FabrizioRomano

[GYST @gystmofos]

@ZwebackHD

[GYST @gystmofos]

@FUT_Accountant England hiring a German coach was never gonna be it 🤦‍♂️😆👎

[GYST @gystmofos]

@ZwebackHD 🤣🤣😥🤦‍♂️

[GYST @gystmofos]

@801010athlete

[GYST @gystmofos]

@ZwebackHD

[Jordi Visser @jvisserlabs]

this is the 17 day rate of change of the MS Tech Mo Factor. -35%, worst in 27 year history.

[GYST @gystmofos]

@6ix9ine @rainbetcom

[GYST @gystmofos]

@michaeljburry So we got a burry bubble, got it

[GYST @gystmofos]

@TheMaverickWS 😆🤣you were wrong shorting this shit the whole way up, and it cost you millions, your own words in your discord, destroyed your followers. Yet now you’re the genius who’s correct on what happens next? C’mon Mav a little humility needed

[Trade Whisperer @TradexWhisperer]

$MU $SKHY $DRAM Just Remember

HBM pricing is expected to nearly TRIPLE by Q4 2027. Not stabilize. Not hold. Triple.

Volatility is driven by fear. The thesis is driven by data.

[GYST @gystmofos]

@RJCcapital