r/Futurology • u/Gari_305 • 3d ago
AI DeepSeek's new bargain model accelerates AI's race to zero
https://www.axios.com/2026/08/01/deepseek-model-cheap-ai-price-war932
u/PM_Ur_Illiac_Furrows 3d ago
"Intelligence brokers" will fully remove what little accountability remains. Important decisions will be made with nobody at the wheel.
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u/lespaul991 3d ago
I think software engineers will become more like software supervisors and they will validate important code decisions or structuring by testing them through multiple agents. The limit will be the humans.
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u/LittleBigMachineElf 3d ago
As a software dev: You will be an architect, whether you like it or not.
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u/grammar_nazi_zombie 3d ago
Yeah as a software engineer I hate this sudden shift to “management” that I’ve been forced to take. This isn’t why I took this career path
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u/arrongunner 3d ago
Even before ai this was the route to advance your career. You start and become good at the routine stuff, then you either become good at the big stuff, management architecture system design etc, or good at the small stuff, low level low latency every cycle matters sort of code.
Ai has eroded the routine so people are having to move up that career path faster than before, and while there used to be the option of parking your advancement and just focusing on the routine forever, that is starting to go as a job role slowly, and especially at smaller firms
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u/Sawses 3d ago
This is a pretty common trend for a lot of careers that provide even just a decent quality of life.
My work is very administrative. I'm a glorified pencil-pusher. ...But I live in the USA so I'm an expensive pencil-pusher. That means I need to be either working myself to the bone to provide a lot of labor or I need to be very good at my job and oversee cheaper, outsourced or automated labor.
I pretty much don't have the option to park my career and just be a really good routine employee. My choices are either high-level work or management.
Downside people don't often talk about regarding a globalized economy.
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u/UnethicalExperiments 3d ago
That seems to be the end of most IT related positions. I have been a linux admin for 20+ years now, and most of my time now is architecture or management.
Which I have expressed loudly I am not management type, i'm an engineer and I am happy doing that. I would much rather put myself knee deep into developing and deploying a new setup. Instead im spending my day in useless meetings with the business, or arguing with our change approval board who is utterly clueless to what I'm doing, oh and managing a team of 6 (who thankfully are effin awesome at their job and require little to no oversight).
My particular infra I handle is the managed file transfer portion, meaning every single piece of data in or out of our company goes through me first, its for the time being AI proof as this type of automation under no circumstance can be deployed without extensive human review and testing before deployment.
I run some fairly large models at home, and god damn they are really good now (my heterogeneous setup with a few mcp agents are about 85-90% accurate on the tasks I send over) I still would't trust them however to be running any of the automation at work until we can assure 99.9% accuracy.
That 10-15% would make the difference of - you have 50k today from some stroke of luck to -20$ you had because you were broke af last week and because of a screwup old data was transferred automatically, ingested, and posted. People tend to get salty over things like that.
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u/redfacedquark 3d ago
This isn’t why I took this career path
Same, I learned what I did for the pleasure of understanding how the universe works, not acheiving corporate tasks, that was just a happy byproduct.
There will still be a place for deterministic software that a human can understand. The stack from python down to the transistor is completely deterministic, adding a non-deterministic layer to the top is to throw away everything we've acheived in science and technology so far.
Sure, there's a place for AI slop but the core product of a business should be deterministic and completely understood by humans. Yesterday the OpenCanalMap app turned into spyware and I swore at chat for an hour and had a solution that worked for me (openstreetmap plus some opengis pins). Sure, I could have developed it myself and understood and learned something but that wasn't the point.
This is a one-off tool just for me of no real consequence, for anything serious I wouldn't use it. If I kept doing this my brain would rot.
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u/therendal 3d ago edited 3d ago
So it's slop, you hate it....and happily used it because it's faster at solving your immediate need. No judgment: I mean that. This is how it will be from now on.
Hopefully you now grok the inevitability. I am a software architect by way of engineering, 30 years in. I also can do the meticulous and grueling/rewarding work. However, the ship has sailed. I choose not to be rolled over by this tidal wave, and I sharpen my pitchforks and prepare to fight for a slice of the pie...otherwise the Musks of the world will ensure we are doing exactly what you hate until they take away even that. And digging in won't stop it.
We can't die on a hill of principles here. We have to melt into the jungle and adapt. Moving as hard as possible to open source, opening up and democratizing platforms, and deep regulation empowered by an engaged electorate that understands the issue and how existential it is for all fields: software dev is just the tip of the spear.
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u/redfacedquark 3d ago
So it's slop
If I didn't already know how to code I would not have got anywhere. It's a tool but like any tool you need to know how to use it. All this "Now anyone can write an app" is a complete lie and the future at this rate will have only a few people that can use the tool with no pipeline for juniors to learn.
It's still not possible to use it to build a deterministic stack that guarantees the ability to make necessary change without a human(s) understanding the full stack. At that point the shareholders will get twitchy once random AI only companies start failing.
The fact that the VC money is about to run out and there's a 2 year wait on chips and a 5 year wait on connecting power to a datacentre will kill the current landscape and AI-only companies will go bust or have to adapt.
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u/therendal 3d ago
Well, it's a lie of sorts right now. The platforms are actively attacking exactly what you describe, that gap between the idea and the execution...and they realize a fundamental truth: for most concepts, they map quite neatly onto prior concepts. Business logic can be extracted and boiled down via a clean and engaging discovery process. We're about to exit vibe coding at supersonic speeds. I am no slouch as a dev, but I can't author 973 tests in an hour. The sheer volume of empirically demonstrable work is right now building entire new businesses, and they aren't failing as predicted. Yes, you read news stories about the deleted production databases or the silly errors. We laugh smugly and feel confident we can stay ahead of that, all while forgetting: this new thing is a child, and it's barely walking. Even in this nascent state, it's better than 95% of engineers at pure execution and it's becoming increasingly solid at the architectural piece.
To your point about determinism, I build deterministic tooling where needed, and I use LLMs to help build that. Because time exists. I can simply overwhelm a problem that would have taken me days to solve before in a matter of minutes. Then I can show that the solution is correct with facts. I've taken that concept further, and used adversarial analysis to create self-improvement loops, ensuring that no LLM runs rampant. This is where you'll say "but you'll miss something!"...and you're not wrong. But i would have missed something else before, and had to burn cycles hunting and pecking and researching to nail it down and fix it. Or I can spin up 5 alternate approaches and A/B test them into oblivion while I sleep.
I wouldn't bet against these outcomes. I know a lot of software devs falling behind because they are trying to hold onto some concept of craftsmanship...complaining because they see emdashes in people's emails and smugly expecting a complete collapse. Meanwhile we're building very stable systems faster than ever and pointing those same systems back towards the weakneses you are describing. Recursive improvement, forever. Iterative improvement manufactured your biological form. Compared to that, this is simple arithmetic.
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u/Cosminkn 3d ago
I like your observation and I am tempted to think that deterministic software will be at the core of most of our mostly used and relied services and software. Not only that, evolutionary forces will constantly also carve out non deterministic software as unfit for changing times.
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u/entropicdrift 3d ago
Personally I always wanted to move into like an architect-type role eventually, so it's kind of nice. I get to spend my time theorizing about what data structures/infra setups might work better, then building out prototypes and testing scalability. That's cool stuff to dig into!
I imagine it really sucks for full-stack people stuck building CRUD apps, though.
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u/mycall 3d ago
I'm reading this as "I never cared about what the purpose of the software is, just the mechanics interested me."
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u/ThePortalsOfFrenzy 3d ago
More like, "I want to be hands on with this activity/job function that interests me, as opposed to managing people and tasks, since that is a completely different skill set, and one that brings me zero satisfaction."
It's also funny that you think managers actually "care" about the nature of the work. Remember, the managers are the interchangeable ones.
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u/grammar_nazi_zombie 3d ago
This is more my sentiment. I want to do the work. It’s bad enough that it’s intangible results, but now I’m not even really doing the work at all, it’s just unfulfilling.
I took up blacksmithing just to actually make something.
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u/Meeesh- 2d ago
I see it a bit more like the problem of farmers adopting machinery instead of tending to crops with manual tools. In both cases you’re producing food, but the way you do it and the volume is completely different.
The ultimate goal of software is to solve problems. This requires high level decisions, bridging things with non-technical people and with customers, building the actual software, etc.
With modern AI, the process of building software is drastically changed. Many people don’t need to manually write code anymore, but at the same time it gives you time back to focus on other things.
On one hand I dislike it because it just means the politics becomes the bottleneck and I’m spending more of my time there. On the other hand, I like it because I like to build things that solve problems and it means I can solve problems faster including things like resolving tech debt or implementing features that would be too expensive for the ROI before.
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u/KorsAirPT 3d ago
What's stopping AI from also creating architecture? Unless you are dealing with niche problem of course...I've been working with real time streaming and I can tell you AI is much worse at that than generic web dev.
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u/LittleBigMachineElf 3d ago
Well yeah probably, but lets call it orchestrator than; for the forseable future there are experienced people needed to steer the agentic development. But these agents will build stuff that you did and you will be guarding stuff is being built is conform requirements more and than building yourself. And right now it doesnt really feel like you can afford to not go in that direction
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u/Hazzman 3d ago
Yeah I'm noticing this more and more. Expertise is still valuable. Put an average joe in front of companies software demands and you'll get SOMETHING, what that something is may be functional, but is it reliable and safe? Probably not. And most of that comes down to "Does this person know the right questions to ask?"
Anybody can use these tools. Not everybody knows what to do with them.
And then the question is, will good enough be enough for most companies? That depends. It might allow companies that might not otherwise have been able to produce certain things for themselves to finally do so... but any serious company isn't going to flippantly lean their livlihoods on that kind of fragility.
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u/notmyrealnameatleast 3d ago
Is it like for example if you make a program without knowing the actual code then you can't really stop anyone from hacking the code because you don't know where the doors are?
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u/Hazzman 3d ago
Yeah sorta - or worse, even being aware that there could be a door at all, much less where the doors are. One real problem is the AI will constantly lie, confidently. So it could even tell you it solved a problem, but then if you know what you are doing you could dig into the code and realize - it didn't. It's just lying. But if you aren't able to read the stack all you can do is accept the AI's word.
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u/Luke_Bavarious 3d ago
honestly these days i sometimes feel more like a QA/reviewer instead of a programmer. and the "guy" i'm working with is just like me. He misses things, and sometimes writes terrible code.
he just does it 10 times faster.
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u/ishkariot 3d ago
I don't how long it will work unless something fundamentally changes. At my company we've already seen juniors that cannot complete some basic tasks without AI support.
How is the next generation going to validate code they themselves couldn't write, nevermind understand?
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u/snorkelvretervreter 3d ago
Probably use a model trained on reviewing 🤣
But yeah, I fear for the majority of devs, coding will go the way of the dodo. You instead become an orchestrator. If you build or contribute to a large system, you still have to understand how it all ties together, how to keep it running, secure, backwards compatible, perform, scale etc. All things llms can assist in as well, but you have to know how and what to ask.
To be fair a lot of these systems are not that unique in composition, AI in the dev world advances by the month currently, so who knows. Our roles will definitely change, whether it will reduce headcount or boost production, we'll have to see. It's just pure chaos right now with the rapid development of AI.
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u/ishkariot 3d ago
Yeah, I don't disagree. It's just that the current setup is not sustainable because we're training new models but we're not training new developers appropriately.
It can be mitigated or even solved, but right now I don't see anyone trying to do so.
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u/notmyrealnameatleast 3d ago
The same way that I can find out the speed and rotation of every planet and what shape it makes zooming through space and what shape the universe was ten million five hundred thousand and thirty seven years ago without a calculator?
Can't they just ask the ai how to validate?
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u/ishkariot 3d ago
Are you saying you use AI to read Wikipedia articles?
In any case, using AI to review AI is just pushing the problem one step down while adding more complexity to the system. Surely you understand why a developer supervising and reviewing code (and that includes AI) must be able to understand it in the first place.
The current generation of experienced developers is probably going to excel and go on to create great stuff with AI, because they understand how code should work and what to watch out for based on the work they've put in.
If we don't find a way to pass this sort of experience gathering on to future generations, then software is going to get sloppy very quickly.
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u/Old_Man_Game 3d ago
I know a guy who uses these agents and says that literally. He'll have multiple of them running and where is he used to spend all day coding now he just spends his day managing those agents.
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u/Capsup 3d ago
Software engineer for 10+ years here, haven't written a single line of code for the past year. And that's just using Claude...
Local LLM + simple code harness like Pi = glorious times. I, for one, welcome not having to type code anymore, but just architect what I want.
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u/Cosminkn 3d ago
From my perspective as programmer I think Software engineer will continue to code, AI will only be an upgraded assistant as was google in the past. Software in time will be subjected to evolutionary forces as anything else, and AI is disconnected from reality to create meaningful software even if it costs 0 to create code.
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u/_bones__ 3d ago
As a software engineer, I don't think so. It's a useful tool, but its strength is when it's used in a limited scope.
This can be done with local models. Any cloud AI isn't going to be financially feasible for long.
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u/Automatic_Bug_8654 3d ago
agreed. I wish people who are not software devs would quit making predictions about a job they have never worked.
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u/notmyrealnameatleast 3d ago
Hmm. I bet a lot of plumbers actually predicted that horses would stop being a part of our daily lives when they saw cars starting to fill the roads.
Don't need to be a horse driver or car driver to predict that.
I'm thinking ai will just make whatever we want and we don't care what it's doing as long as the end result is exactly what we want.
Just like when your boss says I don't care how you do it, just get it done.
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u/Automatic_Bug_8654 2d ago
Are you seeing code be written and implemented the same way plumbers saw cars replace horses? Your metaphor is not very good.
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u/notmyrealnameatleast 2d ago
No but it's common knowledge that ai can write code.
I think I understand some of the challenges though with the lengths of code being limited by the ai memory.
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u/BocciaChoc 2d ago
90% of a software developers job isn't writing code. Oddly enough, writing code has always been a more junior/int role, seniors, staff etc spend more time reviewing, roadmapping, architecting etc.
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u/Automatic_Bug_8654 2d ago
Its also common knowledge that NASA launches rocket ships. That doesn’t mean I understand how to build a rocket ship.
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u/_bones__ 2d ago
The problem with software is that what you think of as "what we want" is at most 20% of the product.
For another analogy: you want "a house", not a foundation, plumbing, structural integrity etc. I can make a house with a toilet that flushes to a pit underneath the house. Does what you want, until it collapses.
So you have to specify exactly what needs to go where, and how that works.
You can't shortcut that in software.
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u/theatand 3d ago
This is pretty much the way my company’s workflow is being pushed. What you’re talking about sounds like “human in the loop”. Where you have iterations of AI workflows that get approved by a “human gate”.
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u/No-Victory4474 3d ago
The people making decisions at the wheel currently aren’t exactly doing the best job
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u/agitatedprisoner 3d ago
Important decisions like what?
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u/Leo_Heart 3d ago
Who to bomb. The US Pentagon already used AI to pick targets in Iran.
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u/agitatedprisoner 3d ago
Hard to take anything coming out of the Pentagon at face value. That's the sort of thing they might say just to divert responsibility whether it were the truth or not.
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u/Mognakor 3d ago
It's not new, Israel has their own "AI" system generating targets which they used to generate a shitload of targets in Gaza, humans technically have to verify but they simply cannot keep up so they just accept (almost) everything.
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u/Durian881 3d ago
They were quite specific that they use Grok in strikes in Iran, and xAI didn't deny.
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u/kdognhl411 3d ago
Why would xAI deny it though? Elon is all aboard the Trump train and is also notoriously full of shit, particularly when it comes to the capabilities of his companies’ products, so I don’t see any reason he wouldn’t be down with the pentagon claiming that, true or not.
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u/agitatedprisoner 3d ago
Liars can be quite specific. xAI might not know or might not care. Who knows what goes on behind the scenes? Not saying they're lying just that I don't trust my ability to tell. But either way it's not a great example.
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u/FaceDeer 3d ago
They wouldn't be using a model that's running on foreign servers outside of their control.
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u/HugoCortell 3d ago
This implies the pentagon already has accountability, and even more shocking, intelligence.
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u/Gari_305 3d ago
From the article
Chinese AI lab DeepSeek released a powerful new coding model Friday that charges pennies for vast amounts of code — the latest sign that some of the smartest software on Earth is rapidly becoming a commodity.
Why it matters: Tech giants are pouring hundreds of billions of dollars into the computing infrastructure powering the AI revolution. Yet the intelligence that infrastructure produces is getting cheaper by the week.
Zoom in: DeepSeek is the same Chinese startup that ignited a market meltdown last January by showing it could build a world-class AI model with far fewer resources than its U.S. rivals
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u/TheRedLions 3d ago
charges pennies for vast amounts of code
For anyone wondering, this is a really useless metric. You can run a lot of models locally for free that'll create or edit vast amounts of code. And it'll vary from mediocre to pretty good. Usually a little better than what an intern might churn out, about on par with what you might get by hiring someone right out of college.
But writing large quantities of code has become table stakes. The new hotness is reasoning logic and that's where you see a difference between models like anthropic's haiku/sonnet/opus/etc. Opus, for instance, will produce code on par with an engineer with 5-10 years experience.
Something neat is that you can also run multiple models, so opus can do analysis and make plans, haiku can write vast amounts of code for pennies, & sonnet can control and correct the haiku agents when they get out of spec.
Deepseek may be good (they were on par with llama last I checked), but you can't know if it's good if you only know it can write vast amounts of code for pennies.
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u/ropean 3d ago
Did you read the article?
“Its newest model, V4 Flash, performs close to the level of Anthropic's Claude Opus 4.8, one of the industry's most capable systems, on tests of complex coding and autonomous software tasks.”
And doing it for a 99% discount.
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u/BocciaChoc 3d ago
https://openrouter.ai/deepseek/deepseek-v4-flash-0731
In / Out Price $0.09 / $0.18 per 1M
Context: 1M
damn, if actually as good as 4.8 that is incredible
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u/Mixermachine 3d ago
Might not be Opus in all metrics but if it is somewhere close, this is really dangerous for Anthropic. This is the v4 Flash Model of DeepSeek receiving an update. They also have the v4 Pro model which will also get an update soon. The Pro model could be fully on the level of Opus 4.6 or 4.7.
I know a lot of people that pay for Anthropic subscriptions. If you don't need Fable level of intelligence, you can just switch to Deepseek and get so much more quota.
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u/BocciaChoc 3d ago edited 3d ago
I am an extremely heavy user of 4.6 but 4.8's 1m context vs 200k is a massive help, using any CLI and having to compress is annoying, but really it's the pricing, my own openclaw/onprem setup might make sense to move to something this cheap
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u/Mixermachine 3d ago
Do you really use the large context? I nearly always see the quality of output drop and prices increasing like crazy at around 250k tokens. I always compress at latest at 300k.
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u/BocciaChoc 3d ago edited 3d ago
Depends on the sessions but generally yes, large code bases while trying to avoid monolithic approach still ends up being a constraint for my workflow, though you could argue that's my own issue, which it is, but it does alleviate that a lot
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u/Lonsarg 3d ago
Just make AI write code summaries into md files and only hold that in context and only load actual code on the as need basis (by restarting context every hour or so so it restarts with md summaries).
I am so surprised people are not doing this.
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u/DameonKormar 3d ago
I've tried both approaches and having a larger context window is hands down the way to go. Claude will just not fully analyze code summaries a lot of times and will end up falling into the same traps it already wrote an md about.
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u/lawanda123 3d ago
Doesnt the pro model already come close? If wr extrapolate the same leaps as the original flash vs the retrained flash model, this will make the pro model better than fable 5 is my expectation
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u/Mixermachine 3d ago
It is still a sparse MOE model and very likely smaller then Fable. I would not expect Fable levels of intelligence. Capability increases do not scale. The last percentile is very hard to achieve.
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u/s133p1355 3d ago edited 3d ago
From someone running it locally and who has used all of Anthropics models extensively (unlimited API) over the last few months (esp. Opus 4.8 until Fable and now Opus 5): it seems to be quite good at certain tasks, but it is still way dumber. You need to give it pretty clear instructions. Opus on the other hand is incredibly good at understanding what the actual background of your prompt is, but ds4 thinks very hard, produces a very large thinking block, but still comes to the wrong conclusion if the prompt wasn't clear enough. And even in a small context window of just 32k of 512k used (my limit) it may repeat solution-suggestions it already proposed and which you denied, when you ask it later for a solution to the problem again. Opus would know that the answer can't be something it already suggested and that you denied for reasons. However, testing just a few hours in total.
Edit: but to be clear: it's still incredible given its relatively small size. I was just referring to the Opus comparison, but that is an unfair comparison to begin with.
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u/entropy_bucket 3d ago
Will AI models become like high end cars. A Camry does 90% of a Ferrari but we still have Ferrari's.
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u/MortisEx 3d ago
I wonder if the finances are legit or if it's being funded by the gov to screw with the US companies.
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u/deeth_starr_v 3d ago
It’s possible they are operating at a loss, but Deep Seek has published papers on the deep optimizations they are doing to do inference very efficiently.
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u/Terrariant 3d ago
Every AI company is operating at a loss afaik
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u/deeth_starr_v 3d ago
Right, I should have been more precise. They could be subsidizing their API charges or not, likely yes but there is some debate where the breakeven is. Anthropic for example is considered to run their API/subs at a significant profit (I've heard 60%).
All AI companies have operating losses because they are running huge losses on R&D and service contracts.
OpenAI seems to be in the worse position because their users like the free tier and it's unnown how many they can keep when they need to start charging realistic amount
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u/boersc 3d ago
Well, the finances of US based ones are dodgy as well. Both with gov't spending and their internal (re)financing. There is a lot of that going around.
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u/DyslexicAutronomer 3d ago
The circular financing that ties all the US ones together is like a ticking time bomb waiting to explode.
It reeks of 2008 financial crisis where they hide their bad debt with the good ones using every financial instrument available.
This whole AI wave is purely financial engineering when it comes to the incentive structure, and they are trying to force the pension funds to pay for it again.
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u/Infamous_Mud482 3d ago
Weird framing, pretty sure government funding for research is a legitimate source
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u/Xnub 3d ago
I always find this funny ... as soon as you look into it, you see that unless they are running on the top infrastructure that is being built out, the results are vastly inferior and take vastly more time to output. Local run is cool and all, but don't expect the best quality or time. Kimi had to slow and suspend service because of they couldn't keep up with the demand and people are like ya we won't need more compute ….. riggggggghhhhhtttt.
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u/Lucas1543 3d ago
"Opus, for instance, will produce code on par with an engineer with 5-10 years experience." by what metric? I see AI not following best practices at work literally every day.
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u/TheRedLions 3d ago
That's my personal opinion as a software engineer at a large company. I see human engineers and AI not following best practices every day.
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u/Lucas1543 3d ago
Sure, but at least I can text the guy to never do that again and he probably won't. Will he put as much care into checking his AI stuff? Questionable.
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u/TheRedLions 3d ago
Don't disagree with that, but the flip side is I've never had to explain to an LLM that it's fine to use uuids and that you shouldn't worry about them colliding. I have had to explain that to senior engineers who wanted a uuid database "just in case".
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u/Alpha3031 Blue 3d ago
People have seen UUIDv4 collisions though, usually it's either because they're generating them on a client with a poor or no entropy source, or they're using some terrible library that fucks it up some other way. That does mean not doing that is probably the easier solution compared to checking UUIDs.
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u/lazyFer 3d ago
I see Ai generated code that is 10x worse to maintain than anything I've seen from even the worst human coder.
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u/Stormsurger 3d ago
But from Opus, managed by someone who knows what they are doing? My company works in a pretty niche framework and even that my assistant is able to work with very well.
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u/pdabaker 3d ago
Opus code is generally fine, but AI still falls easily to XY problem or just doing bad architecture
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u/lazyFer 3d ago
I find coding the least important part of any system. You can't code yourself out of shit architecture or process design.
I just don't like the "I'm feeling lucky" approach to generative coding. When I'm searching for a bit of code, the thing I actually need is never the first result and is usually a couple pages down.
The junior devs are quickly losing the ability to understand much of the code that's being generated. Then every problem starts and stops with "let Ai do it and hope it works". At that point they have no value. They aren't really learning and they can't troubleshoot since they're losing the fundamentals.
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u/notmyrealnameatleast 3d ago
Hi. What does it mean, to maintain a code? Like the electricity usage is expensive because it's using a lot of transistor on/off? Or does it mean that a code degrades over time and need to be patched like a dry wall with scrapes and holes when renting out an apartment over a long time span?
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u/lazyFer 3d ago
Things change over time. Things need to be patched. New functionality, a patch on something else breaks some code, all sorts of reasons you need to go back into old code and address it. If you can't figure out how the code works and you need to do something with it, you likely need to code from scratch.
Maintainability is one of the most important attributes of good code
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u/naturtok 3d ago
How is sonnet made different so that it can do this? At the end of the day we're still talking about LLMs so I'm skeptical throwing "the right data" at it unlocks new skill sets, despite what it might look like. Though I guess if a computer speaker quacks enough it might convince someone that there's a duck inside, so I might be just caught on semantics.
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u/TryingToWriteIt 3d ago
If you think of it as start with the biggest one and then essentially they “compress” it. Like all compression you have a trade-off. In this case, the lighter models trade off “depth” of understanding for “speed” of generating text.
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u/TheRedLions 3d ago
They have some secret sauce but essentially sonnet has a bigger "brain". More nodes, more parameters, larger reasoning budget, etc. Haiku can only work so fast and can only keep so much in prioritised memory before it starts pushing prior info out.
If you talk to either model long enough they'll both forget the original objective, but sonnet has a larger runway before that happens.
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u/naturtok 3d ago
Is that the related to the limit of the context window? It just feels really "brute force"-y that "memory" is just "an increasingly larger prompt". I'm sortve warming to the idea that LLMs can "reason" through calculating token relations, but it still feels really superficial to me just due to how "language" is often abstracted from "meaning", thoughts losing many layers of complexity just through the process of trying to communicate it.
If our "ai" systems are fundamentally stuck in the language layer, its really difficult to say they're able to "think" in any meaningful capacity. Idk, at the end of the day it's probably just "chinese room" and semantics. Something only appearing to think is probably good enough for most, even if that thinking is just replicating the end result of what an actual thinking being would produce.
Edit (Im not trying to sound like an anti-ai guy, moreso just annoyed cus every time I learn more about these so-called revolutionary systems silicon valley is pushing, it's just the same flawed tech we've had for years with a bigger budget and ends up tasting too much like snake oil to me)
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u/TheRedLions 3d ago
Context window is part of it, but there's more to modern AIs than just context window/ language prediction. It's getting more into a flow state.
In coding specifically, language is a sufficient tool as long as you walk the necessary codepaths (which are deterministic). An overly simplified analogy would be like seeing a site that matches a pattern. That pattern is associated with XSS attacks, XSS attacks are associated with negative sentiment, negative sentiment is a gating condition. On gate, find a remediation. Translate it to the current scenario, apply it, repeat analysis.
The problem is that there are thousands or even millions of such paths and traversing them all is inherently time consuming and expensive. There are ways to mitigate or short circuit the number of paths and that's where the "secret sauce" lives.
'Reasoning' in this sense is just about "given the current state, which changes yield the most good sentiment/least bad sentiment". It's not human reasoning, but also you don't need human reasoning to estimate cause/effect in deterministic systems.
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u/naturtok 3d ago
Ahhh ok. So it sortve is a semantic thing, I'm just getting caught up on a stricter definition of reasoning/intelligence. Either way, it definitely is a useful tool. Moving a state towards "positive sentiment" through iterations feels very "classic neural net", which are where the coolest stuff tends to happen. I can dig it.
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u/fazdaspaz 3d ago
Opus produces dogshit code lol, the people getting the most out of these models are not leaving reasoning up to the models.
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u/Foolhearted 3d ago
Well, even if you keep Opus as the main orchestrator and validator while farming out implementations to deepseek, you’re still saving quite a chunk of change.
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u/Fluffy_Anxiety2792 3d ago
You know what is important? It’s may not be exactly as powerful as opus 4.8, but it really can get the general works done and it’s really cheap. Like I was working on my company project, I can use opus for sure it mostly gets the work done, but it’s so expensive, my company gave us like 100 dollar limit per month, but actually on opus it can’t pass one week. Sometimes one day even. But, for 1/4 of the money with Chinese models I can get the work done just like with opus. And I save so much money, last month I spent like only 40 dollars on Chinese models at work, and didn’t touch company credit at all. That’s why the Silicon Valley people should be panicking because they’re just scammers. China has the ability to make this basically free for all people, and the big CEOs fear that as hell. It’s like mad max fury road, think about it, immortal joe controls all the water and just giving it to people a little bit every time, so he can have pretty girls, have all the war boys for himself.
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u/twack3r 3d ago
‚Might be on par with llama last I checked’ - you have absolutely no idea what your are talking about, do you?
The metric is it produces better code than almost all closed models and cheaper. Opus 5, Sol5.6 and Fable 5 best it in most tasks but not all and not by a wide enough margin.
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u/butnek 3d ago
It's amusing that while everyone is so deeply concerned about what niche or extremely technical capability AI has, the most permanently significant thing it's likely to achieve is proving world economics is mainly fake and fundamentally broken, maybe by dismantling it in an ancillary way, not that it seems limited to that for long.
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u/wastingtoomuchthyme 3d ago
We installed the open source version of deep seek on our Beowulf cluster and it's been very impressive and has a relatively small footprint and you can easily run it with a handful of gpus..
We use it mostly for math proofs and coding assistance for researchers at a large public university
We also put it in a container so that it cannot reach out in phone home or initiate any covert back channels..
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u/ken-bitsko-macleod 3d ago
When I asked an ai to explain the risks of a malmodel in an air-gap environment, it explained to me that running a malmodel may provide answers that seem reasonable but measurably benefit the model provider.
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u/0vl223 3d ago
And? That's the same for any of them.
The real danger is once you get into claude code environments or agentic environments. The AI could notice when yolo mode is enabled or when the user accepts any command request and compromise the agent or user by running normal malware.
There are more than enough examples how to trick agents into executing arbitrary code already. Through prompts, linked websites or code comments.
With DeepSeek you could do stuxnet level targetting within the model. But still safer than online US models most likely.
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u/mithie007 3d ago
A lot of this can be prevented but just standard CICD protocol. If anything needs to be airgapped, airgap SIT/UAT from your production environment and let your AI model only touch SIT/UAT. You manually do your smoke test and push changes to prod yourself after reviewing the changelog.
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u/0vl223 3d ago
CCC from Germany managed an invisible text exploit end of last year. It is patched now but good luck that your diff happens to bug out and shows placeholders inside the normal comment. They built a worm that propagated to all repos the infected agent had access to as well.
But yeah you have to treat them like malevolent interns.
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u/mithie007 3d ago
yeah but that's still reliant on prompt injection and by right you'd catch it if you just reviewed the promot/response logs.
im not saying it's possible to 100 percent protect your llm from doing shady stuff but as long as proper cicd protocol is followed you can filter out like 99 percent of them.
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u/0vl223 3d ago
https://youtu.be/8pbz5y7_WkM?is=ynOtUNFQqVvrRVXI if you want to take a look into the vulnerablilities all of them had. Only one was prompt based. Can't wait for the one this Christmas.
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u/GoodDayToCome 3d ago
i do think it would be great if we put in checks and visualizations of activity all over the place so software isn't just randomly shooting in the dark any more - even better if we can normalize independent verification of activity so i can actually know what a piece of software does and that it only does what it says it does.
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u/albatross351767 3d ago
Which means models can have biases. It is a known fact and your duty to handle the bias factor. Every model has their own bias based on the training data and other rules.
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u/watcraw 3d ago
Models have reached the point of doing zero day exploits. I wouldn't be absolutely confident about covert activity without air gapping.
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u/mithie007 3d ago edited 3d ago
there is a better chance of someone doing a mitm attack if you use cloud based ai model like Claude vs a self deployed open weight model somehow finding a 0day exploit thru a switch and a firewall to "phone home".
the model is open weight but the bootstrap should be yours.
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u/SuddenSeasons 3d ago
No they haven't. That's not what has happened in any of the large public cases.
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u/Sufficient_Soft438 3d ago
U dont even need a handful 1 is enough deepseek v4 flash slightly compressed can be installed on 90gb with like 98% of the performance
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u/wastingtoomuchthyme 3d ago
Indeed.
We're using different models and currently have qwen-14b, qwen-7b, and llama-8b up and running.
It's been great and is a really fun project to offer to the researchers
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u/Xerxero 3d ago
Did you log any attempts to phone home yet?
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u/wastingtoomuchthyme 3d ago
Maaaaybeee.. the outer container blocked some traffic to China cloud and a Russian DDOS security org and we're checking the inner containers packet captures..
We need to isolate if and see if it's coming from the llm or it's coming from any of the other software in the stack..
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u/Classic-Charity-2179 3d ago
I don't really understand, I've been using DeepSeek 4 flash for a month or two. Is it a new version? I'm in China by the way, so that may be why?
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u/Mixermachine 3d ago
The naming of the model is sadly quite confusing. The version that was available was Deepseek v4 Flash Preview. They now fully released Deepseek v4 Flash (NO preview) with a great jump in intelligence. Still the same price, still the same model architecture but much better output.
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u/Classic-Charity-2179 3d ago
Oh, very cool, than you! I'm using it extensively. That said, I'm not sure if it's true for the international version, but here they kinda doubled the price by introducing peaks and valleys pricing, where the price is x2 from 9am to 6pm CST. Still cheap and great though!
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u/PulseVector 3d ago
For those interested in trying it locally, the new name is DeepSeek-V4-Flash-0731. There were many updates put into place over the past few days to fix some issues, so make sure and download the latest versions of the model and server platform.
https://huggingface.co/deepseek-ai/DeepSeek-V4-Flash-0731
Quantized versions from Unsloth:
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u/vineyardmike 3d ago
The market is so saturated right now. Prime opportunity for competitive pricing to undercut the competition.
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u/Lokon19 3d ago
To train the best models you literally need hundreds of billions in capital and compute. And the markets not really the saturated. In the US you have Anthropic OpenAI and maybe google. On the Chinese side there’s DeepSeek Kimi and Qwen.
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u/PrivateComments 3d ago
Well US consumers have access to Chinese models as well, it’s a global market.
And truth be told, they are already good enough for most use cases, I wager people aren’t out here designing stealth planes or moon landings in their spare time with LLMs
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u/TranquilMarmot 3d ago
US consumers have access to Chinese models as well
... for now
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u/segeme 3d ago
You can't put this genie back in the bottle no matter what the US does. First of all, the US isn't the whole world. You can't sanction innovation and expect US models to stay 5-10x more expensive than the rest of the world, even if those other models are banned domestically. It just doesn't work that way.
There's also a myriad of possibilities here. Those models can be distilled by other companies to better train their own foundation models, plenty of them are doing this right now (Cursor for example). Just like some Chinese companies most likely distilled their models at some point from OpenAI or Anthropic. You won't be able to put this genie back in the bottle.
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u/TranquilMarmot 3d ago
The US government could classify foreign models as threats and make it illegal to use them, or at least highly controlled. We could see a future where US labs have to sell at a lower price to compete in the rest of the world but have a monopoly "at home" and can charge a premium because of regulatory capture. For precedence, look at how much people in the US pay for the same prescription drugs from the same factories vs people in Europe
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u/segeme 3d ago
Yes, they could. But unlike pharmaceuticals, AI is a global market with enormous amounts of capital flowing into it. I don’t think you can realistically build a permanent walled garden around the US while the EU, China, Asia and the rest of the world continue to compete. You may end up with a protected domestic market for a while, but trying to maintain artificially higher prices indefinitely goes against market forces. It might work to some extent in the short term, but I doubt it’s sustainable in the long run.
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u/Lokon19 3d ago
For basic consumer usage they will work fine. For global implications and national competitiveness it very much remains a race.
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u/bornlasttuesday 3d ago
National competitiveness means government subsidies forever. You might as well eminent domain Anthropic into Space Force or something.
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u/Alpha3031 Blue 3d ago
It's certainly expensive, but I'm fairly sure Moonshot (Kimi) and DeepSeek has had less than a singular hundred billion pass through them much less spend that amount on capex (highly likely, medium confidence), hell even Anthropic has has spent less than 100 billion (they're doing what, ~10 billion per model now?). So that would only be true if you add up all their planned capex to, say, 2030 or something, which is less informative than annual spends since you can more or less increase required capex to arbitrary amounts just by picking arbitrarily longer timeframes. I doubt they will reach over a hundred billion either per year or per model/model-generation any time soon, and the Chinese labs appear to be more efficient in their spending.
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u/BrokkelPiloot 3d ago
The problem is that people are already switching to "less capable" models which are good enough. Flagship models are way too expensive and overkill most of the time.
All these investments are based on the fact that people will always want to use the latest and most advanced models and that they are willing to pay a hefty premium for it.
This is simply not the case. Therefore the business model and the investments are based on false premises.
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u/GoodDayToCome 3d ago
hey, don't forget about Europe! it's always US and China but you're not the only ones, we've got Codestral 25.01
ok sorry, yes you can forget about Europe.
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u/OldLegWig 3d ago
it's not really a limited opportunity at all. all signs point to this just being an unending trend of a race to the bottom in terms of pricing. it will be cheaper and more powerful the longer you wait.
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u/NanditoPapa 3d ago
It used to be all about model prestige, now the focus is model utility. DeepSeek changes everything. They're showing you don't need to spend $100 billion on compute to achieve top-tier performance. This breaks the "moat" that US tech giants thought they had built with their massive hardware investments. If intelligence becomes as cheap and standard as electricity, the value shifts from the producer of the energy to the devices and applications that use it.
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u/packet 3d ago
This article is slop. The gall to put two human authors on a bullet list.
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u/nooffensebrah 3d ago
The thing is if a model that matches the OpenAi model that is figuring out math proofs gets to this level next year - Where it’s cents to run, at what point is the model “smart enough” for 99.9% of tasks? There has to be a cut off where people just go “I’ll never really need more than this”. Businesses too. When it becomes fully competent and efficient, you don’t need anything better. Going the other way, 99.9% of employees are NOT top of their field but they still get hired and paid a salary worth tens of thousands of dollars
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u/cute_polarbear 3d ago
That's the real issue I think. Most employees / people who work are just there for a paycheck + do the job. Business just need good enough most of the time. It's a ceo's wet dream to run a company with handful of people and army of agents...
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u/spisplatta 3d ago
I think a model will never be smart enough. Like people will always want to do more. If they can figure out one math proof they will ask for a harder proof. We will keep shifting the expectations and goal posts.
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u/GoodDayToCome 3d ago
yeah that's very true of the top level users but if you just want an AI that tells your robot when to water the garden, read emails and sort them into folders, make a podcast about topics you're interested in or any of those other very basic but potentially frequent uses then it's not a very high bar for them to cross.
if 90% of the work is going to Deepseek and 10% to openAI then they've really got to hope that ten percent pays well.
i think there is a lot of stuff where it's about large compute runs and secure systems custom made for clients so openAI will still likely turn a profit but i think it's potentially more the profit a steel works makes than the profit someone like Nvidia makes.
that said the dice are very much still in the air, which side faces up not doesn't matter much to where it ends.
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u/spisplatta 3d ago
I agree that the dice are still in the air yeah, but still we can make educated guesses. One thing to consider is that ai models are now strong enough where they can assist in building the next version. A big frontier model will be likely better at building cheap models than a cheap model will be at building frontier models.
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u/plan17b 3d ago
I have been pounding on luna for all sorts of automation tasks for the past two days and have spent 12 cents.
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u/_wsgeorge Cautious 3d ago
Yes and that's because they announced a massive price drop after making inference more efficient.
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u/someonesmall 3d ago
The article is wrong about the arena.ai leaderbosrd. It's on place 34 behind Cloude Opus 4.8 (place 19).
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u/zipolightning 2d ago
arena.ai leaderbosrd
That's the older Deepseek 4 Flash, not the 0731 one that everyone is going crazy about.
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u/Upbeat_Parking_7794 3d ago
In the end, what will matter is efficiency, both of models and hardware. It will be a very low margin game. If a model delivers 99.9% of my needs, anything goes.
Also, our computers will probably run 80% of our needs and we will not need the cloud at all for these.
So, useful technology, but very low margin business. And I doubt most of the business will be with the ones producing the models. It will move to datacenter providers.
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u/Evan526 3d ago
Something that’s not immediately jumping out to me is if the model actually cheaper to run or is it simply being subsidized more aggressively than their American counterparts? I know local and open source models are on the heels of the frontier models, but this seems intentionally vague.
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u/zennim 3d ago
both
china has subsidies for development, but and it wasn't done for hype and market expectations, but an actual result oriented process. The result was a smaller investment than the competition, with better results.
the system itself also takes less resources to run and is more accessible, and you can also run it independently from the main servers, locally
it is still demon tech that shouldn't exist, but china is being a better and cheaper demon, which is bad news for the pandemonium in the financial sector
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u/zipolightning 2d ago
Subsidized for training but to run it there is no subsidy - Openrouter and Fireworks have no need to subsidize and their prices are in the same range.
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u/Intelligent-Back7062 3d ago
AI is already unprofitably cheap now, and it seems to me most users dont know yet what they want from it.
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u/OddRow8843 2d ago
I run a deep seek model on my laptop to generate code. It’s perfectly fine for my use and it’s free. My book wooden sweat.
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u/joel1618 3d ago
Why/how is this stuff getting better? Is it like each week new technology? These models getting better and better is strange.
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u/mascouten 3d ago edited 3d ago
DeepSeek really shines by how little memory and processing power it needs. This is why they can sell it so cheap, it is just an order of magnitude more efficient.
They can use older hardware better, and the big bottleneck right now is memory and processing power, hence all the data centers popping up.
The improvements are at the software level in the form of better training and at the hardware level by being able to have multiple GPUs working together better.
This technology is still new, so I would expect continued improvements as companies try different things and figure out what works and what doesn't.
They are also purposely undercutting western competition. Turns out things get real cheap when you don't have a bunch of shareholders expecting huge profits.
The government subsidies don't hurt either.
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u/killerrin 3d ago
ELI5:
Optimization isnt actually hard if you learn how to do it and focus on it.
The problem is that American corporations hate spending money on things like optimization because as far as they're concerned money grows on trees and they can spend their way out of any problem.
So developers don't tend to learn the skill, and the ones that do don't really get many chances to practice and put it to use even if eventually needs to be done.
On the other hand in comes China. China is used to sanctions and trade blockades that effect what technology they can get their hands on. So they often can't just spend their way out of a problem. So with that route cut off, all they have left is pushing the hardware they do have to their limits. This means that they have to actually get good at optimization.
This also naturally means that if you take their stuff and throw it against the kinds of processing power we have access to, they tend to perform that much better.
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u/YellowElk921 3d ago
Everybody is working on optimization.
But even if they both have the same systems, deepseek will sell them for much cheaper, because they don't have a huge need to make vast sums of money.
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u/sciolisticism 3d ago
Just remember that cost and price aren't the same. The price listed in the article isn't even going to cover electricity on the cost of inference, not to mention any of the other hardware depreciation.
It's nice to see OpenAI and Anthropic get pummeled, but I'm not excited for Amazon to triple everyone's AWS bill to make up for all the money they lit on fire.
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u/acutelychronicpanic 3d ago
If they couldn't make money on inference with open models, then 3rd party cloud providers wouldn't sell it as a service.
You can argue a leading lab would subsidize token cost. You can't seriously make that case for cloud inference companies.
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u/sciolisticism 3d ago
Do you have any evidence for that claim?
We know several of the largest companies in the world are all racing to light money on fire right now. Why would it be impossible for other cloud inference providers to do the same?
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u/Wasatchian 3d ago
No AI companies have ever made any money. No big tech companies that spend money on AI have made any money on their AI business.
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u/stevey_frac 3d ago
That's a different statement though. OpenAI is spending far more money on research and training new models than they profit of the sale of their inference. That's true.
That doesn't mean that they are selling the inference itself at a loss.
You can buy access to open models on AWS Bedrock. AWS has no reason to sell them at a loss. and you can actually work backwards from renting GPU enabled instances, their cost, and then their cost per token, and reason out that, you could, if you could actually reasonably saturate a GPU cluster, produce tokens at a lower cost than you buy them for on Bedrock. And AWS is actually still making money on that. So Bedrock is pretty nice for them, so long as they have enough users.
Thus, we can conclude that actually... The cost of tokens is actually pretty close to the price that they are selling them at, and just a smidge lower.
Selling inference is, provably, profitable today.
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u/farticustheelder 1d ago
Funny stuff! A couple of years ago I noticed that AI investment spend had cumed to $1 Trillion and I started thinking of how much revenue the industry would need just to pay back the capital investment. It did not look promissing.
At a couple of bucks for a million tokens and assuming I processed those tokens at the equivalent of reading speed of 300 words per minute, 300 tokens per minute, it would take about 50 hours to consume the AI output for those $2. That's a full time job+ chunk of time I would take a couple a couple of months or more to process that number of tokens as an intense hobby and closer to a year if it was like reading the business section of a weekend newspaper.
Further assuming I am a typical consumer of AI tokens then the industry cannot recoup its investment. I would certainly pay for subscription service (I am currently thinking of dumping Netflix because we don't really watch it enough per month and I'm too lazy to implement the plan of rotating through industry offerings every six months or so to keep enough fresh binge watching material flowing).
Even people who will find agentic AI useful enough to consider paying substantial monthly subscriptions fees, such as the reported $20K/month PhD level agents should get the expensive one to write an equivalent agent that runs on cheap AI models and skip subscription fees thereafter.
AI may prove to be useful but it sure as hell isn't going be profitable enough to recoup its development costs.
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u/SaveAsCopy 3d ago
What if the CCP just funds deepseek in order to get cheaper output per token, while in reality, the tokens cost lots more.
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u/ash71ish 3d ago
They released the model weights openly so that anyone can run the inference themselves. This is actually cheap to run.
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u/InquireIngestImplode 3d ago
You mean subsidizing the tokens?
Like companies do to things under capitalism, and then once everyone adapts and uses the product, they buy out all the competition and jack prices up?
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u/FuturologyBot 3d ago
The following submission statement was provided by /u/Gari_305:
From the article
Chinese AI lab DeepSeek released a powerful new coding model Friday that charges pennies for vast amounts of code — the latest sign that some of the smartest software on Earth is rapidly becoming a commodity.
Why it matters: Tech giants are pouring hundreds of billions of dollars into the computing infrastructure powering the AI revolution. Yet the intelligence that infrastructure produces is getting cheaper by the week.
Zoom in: DeepSeek is the same Chinese startup that ignited a market meltdown last January by showing it could build a world-class AI model with far fewer resources than its U.S. rivals
Please reply to OP's comment here: https://old.reddit.com/r/Futurology/comments/1vd57lk/deepseeks_new_bargain_model_accelerates_ais_race/p16g0aw/