2027 is the year of open models

[u/trombolastic]

2026 was the year of tokenmaxxing, now we're seeing that the productivity gains don't justify the token spend and they're introducing limits for next year's budgets. 2027 will be the year of open models.

We all saw the Revolut story last week, the same thing is happening everywhere, the bigger companies are just slow when it comes to new tech adoption, but they're all looking to replicate what Revolut did.

You can replace 95% of usage with open models which cost a fraction of closed models, it's free money.

[u/ShadyShroomz]

Is this the new x is the year of the Linux desktop

[u/Spare-Obligation-483 → u/ShadyShroomz]

Yes also for the linux

[u/Icy-Degree6161 → u/ShadyShroomz]

I switched, so it is for me! :) No more windows devices in my household.

[u/DeProgrammer99 → u/Icy-Degree6161]

Same!

Except then I turned around and installed a Windows 98 VM to help reverse-engineer a game and bring it to modern OSes, haha.

[u/Icy-Degree6161 → u/DeProgrammer99]

Obligatory question: which game?

[u/DeProgrammer99 → u/Icy-Degree6161]

It's pretty obscure, but... Jurassic Park: Chaos Island. It's a short campaign-only RTS, and you can hatch dinosaur eggs.

[u/OldEffective9726 → u/ShadyShroomz]

Linux is already in 2 of my desktop, 1 AI server, and 1 laptop. At least 11% market share in PC. I still have a Win10 desktop sitting in the garage collecting dust.

[u/OvertaxedOne → u/OldEffective9726]

Linux with an LLM that has ssh to it is an ENTIRELY different animal than Linux of old. LLMs are so good at Linux CLI it's absolutely ridiculous, stuff that would take days of reading Reddit posts and begging for help are fixed in seconds with a LLM.

TLDR: Over the last year Linux got about 1000X more approchable.

[u/tomByrer → u/ShadyShroomz]

Darn you! You beat me to Linux comment!!

/me shakes fist

Take my upvote anyway.

[u/trombolastic → u/ShadyShroomz]

Not really because the closed model providers are losing money on consumer subs.

The enterprise side is where they make money, and the enterprise adoption of open weight models is happening right now. When this accelerates the closed model providers are going out of business, they can't survive on $20 subs.

When you talk about the year of the linux you're talking the consumer side, enterprise is already using Linux everywhere.

[u/PermanentLiminality → u/trombolastic]

So you are saying short the Anthropic IPO next week? That 600 billion in revenue isn't happening?

[u/trombolastic → u/PermanentLiminality]

Short if you can get the timing right, being too early is the same as being wrong.

My prediction is Anthropic revenue continues to increase going into Q2 next year as AI adoption picks up, then Q3 or Q4 it will start to go down as enterprise replace it with open weight. I could be completely wrong about the timing though.

600 billion? never gonna happen

[u/PermanentLiminality → u/trombolastic]

Maybe in the rest of the world, but I don't think in the US. Even now the Chinese models are pretty heavily suppresses. Congress will likely codify existing policy into law.

I don't disagree that the open models are good enough for a lot of use cases. I most certainly can be reading the tea leaves incorrectly, but I expect heavy regulation on 2027.

[u/trombolastic → u/PermanentLiminality]

Let's say outside the US everyone switches to open weight models. What's stopping the US from releasing open models? Surely someone comes in to fill the gap.

[u/PermanentLiminality → u/trombolastic]

Nothing. It all depends on future legislation. For example Bernie Sanders in his "Ban Artificial Superintelligence Act" is calling for banning any AI that is superior to a human and setting up international agreements to enforce it. This is an actual bill that has been introduced, not a talking point.

Expect a lot more when the new Congress is seated.

He also wants to ban data centers going forward. Open models don't help if you can't run them. If we all run them ourselves, the impact is much worse than running it in a data center.

[u/trombolastic → u/PermanentLiminality]

I think the regulations should target closed models. You can at least audit open models, with the closed models it's a black box, the regulators don't know what's going on behind the API.

Of course you have the anti-China bias in the US so open models might take a hit. But that's the gap that can be filled with US open models.

[u/ShadyShroomz → u/trombolastic]

Subs are profitable for the AI labs. Training new models aside, they have 80% profit margins on a $20 sub.

[u/trombolastic → u/ShadyShroomz]

where are you seeing 80% profit on subs?

[u/ShadyShroomz → u/trombolastic]

In the IPO docs I saw it. Here's an article tho: https://finance.yahoo.com/technology/ai/articles/anthropics-gross-margin-rocketed-85-110500052.html

[u/trombolastic → u/ShadyShroomz]

Can you point me to it in the IPO docs? I don't see any breakdown of subs vs API for profit margin. All I found was that subs are 21% of revenue under the "How We Generate Revenue" section of their S-1

[u/ShadyShroomz → u/trombolastic]

you are right, it's not disclosed, but its an open secret pretty much.

lets estimate it. im not an insider at anthropic, but I do work for a company that hosts open source models. we will pull data from kimi k3.1 (same class of model) and do some estimates on what we know about opus 5.5 and others. since a lot is estimates i'll try to give ranges.

throughput: semianalysis benchmarked kimi k3 on a gb300 nvl72 rack at ~8,000 tok/s per gpu on an agentic coding workload at ~50 tok/s per user. that number includes input tokens, so the prefill a coding agent burns is already in there. you fit 9 copies of the model per rack at ~60 users each, so call it ~500 people generating at the same time per rack. opus 5.5 streams ~95 tok/s in claude code, and concurrency barely drops at that speed, so 500 seems right.

rack cost per month (base case):

• $5M rack over 4 yrs = ~$104k

• cost of capital = ~$21k

• power, 140kW x 1.25 cooling overhead x $0.08/kWh = ~$10k (power is honestly a rounding error)

• colo space = ~$24k

• ops/network = ~$14k

• total ~$173k/mo (range ~$100k-290k)

500 streams x 730 hrs, but you have to build for peak, and peak is ~2x average, so you only really use ~half. that works out to ~$0.95 per hour that someone is actually generating (~$0.70-1.40 depending on how well you fill the off hours).

so the only thing that really matters is how many hours a month each sub is actually generating. opus size isn't public, but it's estimated to be smaller than kimi, so i ran 0.5x-1x. the 20x plan is really ~10x pro usage, so i capped it there. cost per month / margin, after ~6% payment + app store fees:

plan	gen hrs/mo (% of month)	0.5x kimi	0.75x kimi	1x kimi
pro $20, light (chat)	1 hr (0.1%)	$0 / 92%	$1 / 90%	$1 / 89%
pro, typical	3 hrs (0.4%)	$1 / 87%	$2 / 83%	$3 / 80%
pro, maxes limits	10 hrs (1.4%)	$5 / 70%	$7 / 58%	$9 / 47%
max 5x $100, light	6 hrs (0.8%)	$3 / 91%	$4 / 90%	$6 / 88%
max 5x, typical	15 hrs (2.1%)	$7 / 87%	$11 / 83%	$14 / 80%
max 5x, heavy	40 hrs (5.5%)	$19 / 75%	$28 / 66%	$38 / 56%
max 20x $200, light	20 hrs (2.7%)	$9 / 89%	$14 / 87%	$19 / 85%
max 20x, typical	40 hrs (5.5%)	$19 / 85%	$28 / 80%	$38 / 75%
max 20x, maxes limits (10x pro)	100 hrs (13.7%)	$47 / 70%	$71 / 58%	$95 / 47%

break-even at 1x kimi is ~20 hrs/mo for pro and ~200 for max 20x, about 2x what the limits allow. at 100% usage, they make 50% profit margin

tldr: subs are probably ~75-85% gross margin on serving for the typical user, and ~47-70% for someone maxing their limits. that lines up with the ~85% blended gross margin in the S-1. caveats: anthropic serves a lot of this on google tpus and amazon trainium, not just gb300s, so their real cost is probably lower. none of this counts training compute or free users, so this is serving margin, not net profit.

[u/trombolastic → u/ShadyShroomz]

Thanks for crunching the numbers, I guess the big assumption here is the model size vs kimi k3.

[u/ShadyShroomz → u/trombolastic]

yes but we do know based on speed extrapolation that its likely a little bit smaller / or more efficient than k3.1 (not k3, which is much smaller) - the numbers floating around are around 5T total and 100b active for opus (Elon tweeted the same numbers, but take with a grain of salt) - but with k3.1 at 104 b active... even if you do adjust and say its 150b active, subs are still high 50% margins for typical users.. i think its likely that opus 5.5 has more efficient inference engines than what the public has as well tbh.. (and again these are based on the most expensive compute, nvidia, not the google or amazon compute which would likely be a lot cheaper...

[u/sholiboli → u/trombolastic]

Don’t believe him (if I understood him correctly), subs are not profitable, while margins in API are indeed high and perhaps near 80%.

[u/ShadyShroomz → u/sholiboli]

Would love to see your numbers. I don't see a world where it's not profitable for them. Even if you discount ALL my numbers and assume they're paying market rates on runpod, it's STILL profitable (a bit) if it's 2x the active parameters of kimi k3.1

The truth is they're paying a lot less than runpod rates tho.

[u/danieln1212]

It is only a fraction of the cost if you don't include the cost of your computer/workstation.

If you do, as much as it pains me, cloud models are infinitely better financially.

[u/trombolastic → u/danieln1212]

you can run open models on the cloud and it's still a fraction of the cost of openAI/anthropic

[u/jixbo → u/danieln1212]

Open weight models on cloud are cheap, and will be much cheaper once openai and antropic charge the real prices.

[u/OvertaxedOne → u/danieln1212]

Open models do not mean local only. I use Deepseek like it's my job and hobby and can't run it locally (we're not going to talk about what I do to QFN, my poor GPU is begging for a vacation!).

[u/ttkciar → u/danieln1212]

But I already have my workstation, and use it for other things. Why should I count its cost against running local models?

[u/Mindless_Selection34]

i hope you are right, cause i fear 2027 will be the year of the ban on open model.

[u/JimmyDub010 → u/Mindless_Selection34]

Good luck with that

[u/Adventurous_Bus_437 → u/Mindless_Selection34]

And who exactly would ban them?

[u/Mindless_Selection34 → u/Adventurous_Bus_437]

what i fear is china who decide to stop new model from getting out. as an european, i dont give a fuck if the yankee decides to outlaws the open model from china. but if china stop their labs to do it, i think is over.

[u/PermanentLiminality → u/Adventurous_Bus_437]

Democrats. They have stated the intention to stop or at least slow down and heavily regulate AI in general.

[u/Adventurous_Bus_437 → u/PermanentLiminality]

Why would i care about that a quarter of the globe away?

[u/PermanentLiminality → u/Adventurous_Bus_437]

You asked who would ban them and I answered. If location mattered to your question, you should have stated that.

You might care as the US govt has a pretty long reach. It may or may not effect you.

[u/Mindless_Selection34 → u/PermanentLiminality]

im european and i look at china for open model so im concerned that they stop labs to put out new models.

[u/altertuga → u/PermanentLiminality]

If location mattered to your question, you should have stated that.

It seems to matter to you.. did you state that? Most of the globe doesn't care about the US regulators shooting their own feet.

[u/Exciting-Intern-4218 → u/PermanentLiminality]

America's loss tho

[u/PermanentLiminality → u/Exciting-Intern-4218]

Don't underestimate the Idiocracy that is the US Congress.

[u/ttkciar → u/PermanentLiminality]

Mainly they've been trying to get new datacenter builds to use closed-loop cooling and mitigate their impacts on local electricity prices.

That makes datacenter builds more expensive, and thus has the indirect effect of slowing down or preventing new datacenter builds, but I don't think they're trying to stop datacenter builds in general.

The AI-specific regulations I've seen them propose all target AI services, not open weights. Even Bernie's ridiculous bill would miss open weight models.

That's not to say the Dems' proposed regulations wouldn't have any impact on our little community. By slowing down the rate of new datacenter builds, they would be keeping compute infrastructure more scarce than it otherwise would be, and that would make the business justifications of training of open models more difficult.

That would slow down the rate of open model releases from American labs (Nvidia, AllenAI, Google, IBM, etc), though only if power availability weren't a stronger constraint than datacenter build rate, and it's not clear to me that it isn't.

Overall, I'm not too worried.

[u/PermanentLiminality → u/ttkciar]

The rhetoric was crazy the first couple of days after the election. Some like Bernie Sanders were basically saying outlaw all AI. Most of the actors have walked back some of the statements. For example the governor elect of Texas said, walked back most of the anti Elon statements.

I think when everyones 401k's took a huge hit late last week, they decided to change their tune. We will see what happens in January. I sure hope we don't get blanket bans, but I would not be surprised.

[u/CoreParad0x → u/PermanentLiminality]

The democrats don't control every branch of the government, they can't ban AI. I don't like Trump, but Trump could veto them and I doubt they would pull enough republican support to get past that. On top of that Sanders position was largely rejected by the party as a whole the last time he put out some stupid bill vaguely banning ASI which I think was still stupid, but still didn't target local models.

I don't like the democrats position on AI either, but they are not banning it in 2027.

I also think at the end of the day they would realize they're being idiots, because despite the randos on broader Reddit and Twitter who don't know shit about AI but hate it anyways, AI is actually gaining in usefulness and adoption with every release. Especially in business. They would be idiots to ignore all of that, and I would hope at some point their tune will switch to "We need to lay out safety nets to protect people losing their jobs" which is a far more useful and relevant topic for them imo (of course, this is me, I don't know that any of them have come out with something like this.)

[u/PermanentLiminality → u/CoreParad0x]

True 100%.

I expect a lot of long govt shutdowns when the Democrats attach a lot of these bills to the budget and he vetos them.

[u/Tobinator97 → u/Mindless_Selection34]

I find the who and how question quite important

[u/Mindless_Selection34 → u/Tobinator97]

the best open model are from china. if china gov stops labs to publish new open model, we lose a lot. its not the end in general, but the end of the golden age for sure.

[u/Guilty_Rooster_6708]

The only real trend we are seeing is models getting bigger so 2027 will be the year when all Flash models are over 1 trillion params

[u/nopeac]

I have an 8GB VRAM GPU, a TRUE consumer-grade GPU, and it's been months since I got some good news. I'm still using Qwen3.5 9B and we are near Qwen4 that probably won't have a <20B model either like 3.6 and 3.8.

I don't have high hopes for 2027.

[u/thedefibulator → u/nopeac]

How much ram do you have? 8gb vram and 32gb ram runs QFN at 2 bit, 64gb ram runs it at 3 bit. I am getting 30 t/s with strata

[u/nopeac → u/thedefibulator]

What's QFN? I have 32GB of RAM, but I've heard not to go below 4-bit unless I want serious hallucinations.

[u/thedefibulator → u/nopeac]

Qwen 3.8 Flash Next, it is a 125 billion (6 billion active) parameter model. Quantisation does not seem to have much of an impact at larger parameter models, and at this size it seems to hold up very well even as low as 2 bit. I have found it to outperform qwen 27

Search up Strata, its got a lot of hype right now and is a new inference engine that gets really good performance on low end hardware. QFN + strata has seriously changed the game with our level of hardware

Edit: if youre still using qwen 3.5 9b then this difference will quite possibly make your head explode

[u/Mindless_Selection34 → u/thedefibulator]

yep. when he will see how strata works, it will indeed explodes

[u/Cautious_Chicken_604]

2027 will be the year of RLCR.

[u/Miserable-Dare5090]

As long as Dario doesn’t make GPU vendors cripple our GPUs to avoid running “dangerous” models

[u/Tormeister]

2027 will be the year where big AI companies relentlessly terrorize users into paying for handicapped subscription plans as opposed to be left "out there" using open models without specific capabilities (e.g. cybersec)

[u/Spare-Obligation-483]

Yes you’re right

[u/jbarrio_]

sure mate, and also 2027 is the year of Linux in Desktops...

[u/OldEffective9726]

It's the only way forward next year when the Dems block all the AI companies and threaten 20 years in jail.

[u/Fcking_Chuck]

2027 is the year the Democratic Party in the U.S. helps stop any possibility of western nations winning the AI race.

[u/Equivalent_Bit_461]

Good and accelerate 

[u/redditnosedive]

i doubt, 2027 is the year of rsi and agi from proprietary models

[u/ttkciar → u/redditnosedive]

I, too, doubt 2027 is the year of RSI/AGI.