The state of open source AI
stateofopensource.ai
stateofopensource.ai
The frontier models are an edge and a liability. They're astronomically expensive to train. Without them, their models will fade into obscurity. Their marketing depends on people believing the models are meaningfully different, as people have sweatily argued on this forum. Personally, I'm not convinced there's much of a difference between these models at this point. The harness is what takes these random and hallucinogenic models and make them into something deterministic and useful.
You can compare Fable vs Sol vs Kimi in the same harness if you want too and there are meaningful big differences. I chose all Anthropic ones to be safe from the they were finetuned on different harnesses complaint that would be made from that comparison.
As for your speculation, I think it's hinging on some companies releasing models for free or no big differences between models. In a world with hyperscalers and companies training models you can quickly recreate Anthropic or OpenAI by having an hyperscaler ally with a model training company, train a good/a better model, and not release it.
oh wait
Was it ever even a claim that open source search engines were trying to outperform google, let alone kill it?
Elasticsearch
Just like most people use Facebook or Insta for personal webpages instead of rolling their own, most people will use commercial AI forever.
But efficiencies aside; creation of open models still requires a lot of money and compute from a large organisation which is willing to accept zero return for that spend. This largesse is unlikely to continue forever; so the question is which will crack first, the frontier models’ business model or the fast followers’ generosity?
The only thing that took us down a different path is the vast sums of VC funding pumped into the AI companies.
Historically speaking a lot of inventions have come about without things like VC investment. Either way, there’s probably little point in debating it, just because VC funded companies control the market now doesn’t mean they should indefinitely.
But if they think it's important to their core business, corporations don't want to invest, they want to buy. Source: I used to be involved in corporate venture investing at a top 10 valley tech leader.
Who had to leave to build anything.
There's a reason we let companies specialize in some kind of service and buy it from them.
LLMs aren't looking like they'll be highly differentiated like software, so their market will probably be competitive. What negates the main reason Open Source software exists.
This leaves the price differential between a private third party and an internal initiative as barely more than the cost to train the model[1] - perhaps that's where we'll end up, a centrally trained model will represent an economy of scale that can leverage that difference into a margin it can profit off of but your business being purely profit driven by that training expenditure seems like a ridiculously thin margin.
So where does that leave the AI companies? If their LLMs are off the shelf-once built products they have a strong advantage for casual low usage but enterprise customers will have a huge cost incentive to roll their own - if the LLMs require continuous retraining and the frontier keeps moving then enterprise customers will find a packaged service more attractive and likely continue to subscribe for more accuracy but casual low usage will likely shift towards "good enough" models. It seems inevitable that they'll lose half the market and it seems difficult to discern their long term profitability[2].
1. Costs can, I think, reasonably be reduced to hardware depreciation and energy - if trends continue with cloud resource availability (it's possible this won't be the case if large compute providers start pulling resources offline to build a moat but I think they'd likely prefer the reliable compute income over model income which has several other competitive weaknesses). Hardware depreciation would normally be pretty negligible and equal across different training entities, right now we have a chip shortage but given the demand that can't last too long so I'd consider hardware to be fungible - and energy is entirely fungible - they're both hard to moat.
2. Outside of AGI, who knows if AGI will be or what even counts for it at this point - but I think if AGI isn't a doomsday scenario we fall back to one of the two above scenarios - either the frontier is ever moving and they can retain enterprise customers or the frontier seizes up and everyone can just use an off the shelf offering. In either scenario they don't have a lot of moat to deal with for their products unless they can restrict compute which is why Alphabet, AWS and MSFT are the only players I could see realistically coming out of this as an AI vendor winner and I'm not even certain if it'd be a good idea for them if it'd hamstring their cloud profitability.
These two types of contributions have very different behavioral profiles, and it doesn't obviously follow that the historical success of getting people to collaborate socially on building software for fun and for the benefit of the community will translate in any meaningful way to the necessity of being able to raise enormous amounts of money to pay for enormous amounts of electricity.
Training a new frontier model just costs a lot of money and there are very few companies for whom it makes sense to do so, and even fewer orgs who are just going to gift those kinds of resources to an open source initiative.
Your idealistic of open source may require that, but in practice a huge part of open source is commercial and a large chunk of that is low on collaboration (across vendor boundaries).
I seem to understand open models are mostly coming from China, and the benefit of training and releasing them for 'free' is a powerful geopolitical weapon against the Western/US economy that at this point depends on OpenAI & co. to succeed.
Will the West make open models illegal?
We better not.
> What is the financial incentive to do so?
If we'd been sharing all along (as we should have been), we probably would have gotten even further along in the development of the tech.
Think of everything we could do if every researcher on the planet had first class access to the frontier. No academic fallback models. No crude API access. No limits, but direct access to the weights and the ability to lobotomize, splice, and dice.
We could pour intelligence from one container to the next without paying a tax or wearing a blindfold. All without spilling a drop.
*Open* *Must* *Win*
Other countries in the westen hemisphere, probably not.
I agree that, currently, the Chinese govt is not only allowing but tacitly encouraging open weight model releases. However, I don't see it as an attack. I think it's more of a strategic delaying move to slow the revenue to frontier models while China works to catch up. This strategy will likely change over time.
> Will the West make open models illegal?
In the U.S. this seems highly unlikely due to the current administration's generally laissez-faire approach to tech as well as the U.S. constitution severely limiting the government's latitude to constrain economic activity.
As we saw with the temporary Mythos restriction, there are legal mechanisms to limit tech on certain grounds, but over time such limits are subject to close judicial and constitutional review. The Mythos embargo was also likely driven in part by the administration's anger at Anthropic for choosing to block the DoD from using their products for mass domestic surveillance and warfighting. I doubt we'll see any meaningful restrictions on OAI or other large companies. It'll be nearly 3 years before a different admin is in office and could enact serious limits and by then it will be too late for fundamental bans.
There are vested interests in most governments, such as intelligence agencies, law enforcement and the military, who would prefer to restrict some AI from broad use. As we saw with strong encryption, they'll only be able to delay and constrain, not stop, such a broadly useful dual-use tech. The geopolitical, economic, competitive and civil liberty interests are similar between strong encryption and AI, setting up a similar game theory dynamic. While it can be argued AI poses some potential danger, the specter of any such threat is abstract and not immediate.
On the other hand, the tech is obviously too economically essential and competitively vital to risk 'falling behind'. While there will certainly be attempts to ban, limit or constrain AI, the well-funded, highly organized commercial interests and civil libertarians will deploy lobbying, legal challenges and public opinion to ultimately prevail.
Aren't these the same guys who won't even let us have Chinese cars?
I'm not as confident as you that they will keep allowing us access to technology as strategic as AI models out of China and elsewhere that undercut US models in the market.
To everyone reading, download open models from anywhere as soon as they are released. You really have no guarantee at all that access to those models won't be cut off in the future with the stroke of a President's pen. Those downloads are your insurance policy. You'll always be able to access whatever you've already downloaded.
Valve and SteamOS are a good example of what this idea looks like in practice. (Though they may also illustrate a third thing you need: a privately-run company, that has enough profit, and enough commitment from leadership to the company's vision, that they can make long-term bets without having to eventually bow to investors seeking short-term gains.)
This would be an argument for an organisation developing its own model; but not per se for releasing the weights openly.
The possible explanations (I'm aware of, which overlap somewhat) for spending large amounts of money on models then releasing them for free (i.e. the current Chinese approach) are soft power, marketing for a future paid model business (i.e. competing with the US models for customers and mindshare during the time you can't compete directly at the bleeding edge), and/or a geopolitical move to diminish the value of the US's frontier model companies.
To extend the previous analogy: Valve didn't make desktop Linux viable on their own. A lot of it is owed to another self-interested actor -- Google -- through the reduced need for dedicated desktop apps (largely pushed by Chrome), and various enhancements to wireless and power management that were necessary to make it a viable mobile platform (directly benefiting Android/ChromeOS, but then spreading out to laptops and mobile devices in general, including handhelds like the Steam Deck).
You can see it on a smaller scale in ecosystems like Android -- where handset makers regularly contribute features from their UI skins upstream, so that they no longer need to spend engineering resources maintaining distinct versions of theming engines/notification badges/multiwindow/various other stuff.
On a related note this is an argument for open source models, not just open weights. I think a lot of the diminishing returns relate to the opaque nature of most models.
Seemed believable but not sure where that's true
Chinese AI companies are generally smaller tho and the models they're releasing are also smaller (I think estimates put OpenAI and Anthropic SOTA into trillions of parameters)
It is not so strange that models from certain organizations are always a few months behind.
It’s a very new set of technologies, and understanding what is useful to customers and what isn’t is the whole game. Call it, product taste. There were a million cell phones before the iPhone took over the world. Why iPhone? Product taste. There are a million startups, and only a select few become unicorns. Why? Product taste.
You have tripped yourself up there.
iPhone took over as it introduced something innovative over standard phones, but then Open Source (Android) matched the multi-touch and software differences and Apple's branding, lock-in and design etc have managed to keep it as a big player in wealthier countries. IPhone also came on the back of the massive iPod success.
ChatGPT launched the same innovation vs Google Search, but just like Android Opensource AI is moving fast now.
Android has 72.7% market share at present, Open Source AI will do the same unless the frontier labs can continue to do something new.
The frontier labs are saddled with enormous investor and other debts. How long they can keep innovating by spending so much on R&D and paying there staff very high wages remains to be seen.
Once investors cash out via an IPO, the companies are back down to earth and playing in the real world again.
Us developer types like to pretend like specs are the only thing that matters? If you could have a 10x more powerful model you could only access running locally through your terminal, versus a weaker model through a clean web interface, normies will pick the web ui every single time. Product experience is simply everything, as much as we like to pretend like nitty technical decisions are the most important thing.
So? The benefit of open source is that you don’t have to worry about making a ton of money. You just need to be viable.
Apple: premium product a minority is willing to pay for
Android: standard product the majority use
I’m sure there will continue to be iPhone equivalents in the AI world, premium bespoke models. But the vast majority of people will be happy with a cheaper offering.
More like if you could have a 1.25x more powerful model that you could only access through some weird surveillance megacorps aggressive monetization scheme, or choose from 100 others running open models and accessible through 100 different interfaces pandering to every taste.
Normies will choose the megacorp every time, because that was the one in the tv commercial, and within six months will have left for one of the others in a rage.
The only corporate hope is that the government steps in to ban their competition.
Before that we had touchscreen but they sucked.
---
2002: FingerWorks makes advances in multi-touch technology
2005: Apple acquires FingerWorks and its patents
2007: iPhone launchesIt has the feel of self-improving super-intelligence or bust to me. If you get that, the frontier model(s) run away with a faster exponential. It's a bit like semi with Moore's Law with silicon, GaAs could never catch up. If you don't get it, the fast followers crush the high investment and there's no moat. Not like they can enforce copyright!
The onlly way that happens is if America turns into zimbawe.
I've driven in a LOT of the USA. Sure Chicago, NYC, DC, LA, LV... They're all built up and feel modern.
Try driving anywhere in the Midwest outside of the big cities. Dilapidated carcas buildings everywhere. Urban and rural blight. Only jobs are low paying service work. Its bleak. Like, really bad poverty as a disease bleak.
And its crazy watching it too. They're ignorant (involuntatily), poor, and trapped. And democrats only seem to care about special interest of the week, so these areas vote republican.
I don't have a solution btw. Just something I've seen growing in the last 25 years. And its getting worse, not better.
Great.
When I was younger and it was a new thing it was quite a shock since American media obviously doesnt portray it that way. It is quite a contrast to even how the more run down parts of Canada look.
That's why I personally believe Sanders and Mamdani have found so much success with the working class; they keep themselves separate from the Culture War slugfest that mainline Democrats either voluntarily engage in or let Republicans drag them into.
IMO the vast majority of those "culture war" issues (LGBT freedoms, etc) are incredibly important, but to the average poor rural American it feels incredibly distant from their day to day. I can't put my finger on it exactly but Democrats have a tendency to message on those issues in ways that are either counter-productive or get soundbit saying something moronic. So when Fox News and whatnot say that Democrats are prioritizing other groups over them and message on it day after day, it's not hard to see why that propaganda becomes effective.
That's not to say that Sanders/Mamdani/etc don't message on social issues, they obviously do, but they are somehow effective at not alienating voters who may otherwise latch onto that in a negative way.
I don't have a good solution. Just my observations.
Appreciate clarification, I could also just be dumb today
There are people that have explained this a lot better than I have, but here is my poor paraphrasing to answer your question.
Democrats are a bit less centrally controlled and you have a mix of Progressives/Greens etc.. that would prefer their own party but the closest thing they have is the DNC. Some of these ideas are not universally shared even in the Democratic party but they try to include them all.
Compare this with the GOP, there are also disagreements but until recently has a pretty unifiying message. This makes it easier to rally a base.
I could be off, and stating incorrectly but this is how I see it.
There's a point past which "intelligence" stops mattering as much, and IMO we're already there.
Consider which would be more useful (and profitable for its creator): a model that is 3x/5x/10x as "intelligent" as Mythos, for whatever your favorite yardstick of intelligence is? Or a model that is as "intelligent" as Opus 4.5, but can run at reasonable speed on a typical consumer laptop/cell phone?
A better question is would you settle for o3 now or pay 20$ or 200$/month for fable ? Because o3 quality is available OSS.
It is like the new IPhone, in some sort. At some point come a feature many would like to have, despite diminishing returns.
We will see how long labs can keep up and what the scaling curve look like, but I would be more worried into losing sota status to Chinese companies than letting them take the open non-sota approach.
While the engineering team might need a cutting edge model (with the associated costs), the marketing department will be fine by something that can grammar correct or turn a few bullet points into prose. Likewise you already don't need Fable for Ticket -> RAG -> Reply with Faq knowledge or escalate workflows
That's already the case with other very expensive software like CAD packages were oftentimes you have different feature sets enabled for different employees.
Fable or GPT 5.6 Sol regularly hand off obviously broken features in my mobile app.
QA is the bottleneck.
If vision capabilities and understanding of motion improve significantly, perhaps the models can tell that a list is not scrolling correctly, or a transition not animating as it should.
Sure there will be self-hosters but hosting AI models will always be more of a challenge than running scalable database on your own hardware and specialized hyperscalers will be here.
Open models are indeed very capable, but they will eventually become more specialized to the application to keep an edge. It makes perfect sense that the future shape of AI conforms to the landscape it was born out of.
They are noticeably different. Benchmarks, anecdotes, all say the same thing.
Now, is a ~6 month lead actually worth 1 gajillion dollars? Maybe not.
As these frontier companies have been boasting, writing software is now a negligible cost because the LLM can do it.
IOW, no, their software can't be a moat, because, according to their own arguments, you can use their LLM to trivially clone their software.
Perhaps, but what you can't clone is familiarity, polish, integration, and network effects. These companies desperately need a moat, and so for example all the new additions to Claude's web interface are becoming the products that the vast majority of people will use and be locked into (if it goes according to their plan).
I'm not sure what network effects even means in the context of llm selection.
good luck.
This and I very much miss reading the chain of thought. At least I have it on GLM-5.2.
I have zero quality issues on Z.ai Coding Plan and maki.sh as the coding agent, but I've seen many reports on 3rd party providers that they host heavily quantized versions of GLM models.
Someone can, but Apple has essentially admitted defeat and handed the reigns over to Google.
Oh man, they gave them free reign?
How will anyone reign them in now?
For all intensive porpoises, this is like Babe Ruth, chomping at the bat!
Nvidia is looking like they are ditching consumer markets in favor of enterprise GPUs since nobodys heard a peep about the next iteration of RTX cards. The 60xx series is postponed till 2028.
Nvidias playing a dangerous gamble, in my eyes I see all the frontier labs eventually just only buying Nvidia chips for training and building custom ASICs for a fraction of the cost, longer lifespan and cheaper to host.
This will eat their 5 year gravy train for GPUs vs the 10 to 15 for ASICs.
Yeah, I'm pretty sure AI is going to go insular within the largest companies. This will only be hastened by the growing national security concerns/awareness.
Yes, tinkerers and enthusiasts will continue to make use of them, but frontier companies will maintain near total dominance because they will be the only ones with access to the hardware.
I wouldn't rule out the possibility completely, but it won't be very common.
We're going to see Apple and Google compete over services and AI/OS integration instead, it will probably be years before your OEM takes local models seriously.
Running KIMI on a phone is not possible today and I agree with you that it will "probably be years before..." it is.
But how many years do you guess? I personally do not think it will take even 10 years for the situation to be commonplace.
Do you personally remember how far smartphones progressed in the past 10 years? It's not as long a time as you think it is, the limits of what a smartphone GPU is capable of did not substantially change in that time. Nor did the amount of onboard RAM that we include in the package. This is true even for Nvidia's ARM SOCs, frankly.
Apple, Microsoft and Google all eventually want to enforce OS-level lock-in for the most profitable AI services (eg. their own). It's much more attainable and profitable to use that lock-in to sell you exclusive service integration, the local AI revolution probably won't begin on their hardware.
IMO it won't be possible for the foreseeable future. There's essentially zero possibility that phones will gain the hardware capacity to run today's Kimi, so the only other alternative is to squeeze the power of today's Kimi into something that can fit on a smartphone, which also seems fairly unlikely considering the current rate of progress.
Phones have zero HBM today.
> There are famous laws of growth that put terabytes at just a few years away
I assume you're referring to Moore's law here, but if you are, it doesn't really apply to HBM in the same way, especially in a smartphone form factor where LPDDR is the only practical option due to heat and energy constraints, and a variety of architectural complexities specific to HBM that make a TB of it in a smart phone something far beyond what we can hope for in any timeline we can project today.
Those things can all be done today on a $250 used video card and pennies of electricity
Heck, most large enterprise moved to usage based billing and are still happily paying for it. They are force multipliers for your top talent, and when a top engineer is being paid $500k a year, doubling their output for $500/day is a no brainer.
Take a $10 claude sub and fill it with Fable/Opus for a month (meaning use all your tokens) and then use one of the many token/session recording tools (I like agentsview).
It will show you how much your token cost is at current rates if using an api. I use the $20 plan and I don't use all my tokens, and am around 50x.
I don't think we'll see home users being able to match even the low end clouds for a long time.
Longer term I think we'll see these uses of AI cluster into a few groups:
- maximal code / reasoning quality, at high prices (Fable)
- typical code / agents (sub-Opus, Terra)
- cheap but decent enough quality (think Deepseek / GLM / Luna)
- so cheap I don't care about utilization (Deepseek, and friends)
And also more niche ones:
- ultra fast with high quality answers (typically sub-SOTA). Cerebras / dedicated silicon type approaches, expensive.
- ultra fast with mostly-adequate answers, and an openness to retries, moving up to better models
I think the open models will dominate (not with individuals, but low cost providers) all except the top 1-2 of those categories, and there will be a continuous erosion on the big player's moats. The top categories are also where all the money is, but I'm not sure it can justify those investments long-term. I also think they will have to squeeze more money out of them to justify the investments, which will also drive people down the list.
Edit: clarifications.
But they're not. Meta, SpaceX, Microsoft, Amazon, they're all leasing out capacity to others. If they were truly constrained, we wouldn't see that happening.
i doubt it. it cost money to train a model. we can see that with the price increase for Kimi3. Chinese AI companies is leaving a lot of money on the table for third party providers. you think they going to let go of those money that they can make. sooner or later they will want to collect. after all, none of Chinese open weight model is release by a none profit. its all for-profit companies that is releasing open weight model.
The idea that we can out-parameterize frontier models is a common misconception, the true moat that Anthropic and OpenAI is why Chinese model providers are open sourcing and making it dirt cheap to keep pace through its "proxy chain operators"
1. If market conditions change they might decide to close down like Meta did.
2. If as you said models keep getting more expensive to train, is an open weights strategy financially sustainable?
edit: typo
China absolutely does not have my best interests at heart, but America's technofascism is probably more immediately dangerous and harmful. Americans genuinely have more to fear from America than China at this point.
Fascism was laid out by Mussolini in the 1920s - it amounts to the idolatry of the state.
"All within the state, nothing outside the state, nothing against the state." B Mussolini
Also defined as Corporatism: the union of state and corporate power.
Which country do you think is closer to Mussolini's model ?
It’s no wonder than Thiel & co. are rediscovering Futurism, and blind faith in the machine is basically what Silicon Valley is all about.
> At minimum, social cohesion requires the ability to sustain and motivate a critical mass of the population.
The US is the bad guy on the world stage right now. If you can't see that then you're part of the problem. Dunno what to tell you. Read a book, maybe?
Wikipedia has a whole page on the definition of Fascism [1]. Also worth reading is Umberto Eco's article on this subject, which also has its own wikipedia page [2].
Spoiler alert: it's not as simple as you imagine.
[1] https://en.wikipedia.org/wiki/Definitions_of_fascism [2] https://en.wikipedia.org/wiki/Ur-Fascism
I recommend Umberto Ecco's essay "Ur-Fascism" [1] if you want to get a more accurate picture of what fascism is. It might make you reconsider which of these two countries fits the pattern better, at least at the moment.
The point they were making was that the most successful open models- those coming out of China- are made my companies that are using those open models to get exposure in Western markets. The goal is to undercut the Western dominant players, not out of any particular "open source" philosophy, so it wouldn't be wise to expect them to continue providing open models long term.
The interesting discussion is why they are doing this and why it's "bad". The goalposts are right where they always were, you've failed to see them past your own feet.
And while I use and love the open weight models, it seems likely to be pretty hard to prove conclusively that they have no reinforcement-learning-trained proclivity towards curling specific URLs if the topic happens to be some very specific thing that the government is interested in, when used to drive agents.
So it depends who you are. If you're a company, you might have something to fear. If you're a private citizen, maybe not so much.
Provenance of training set is going to be critical. It’s largely ignored now, but the first time a malicious exfiltration occurs it will go off as if a bomb was detonated.
Until very recently there would have been little point. What could China do that the US couldnt?
I'm sure the US will start to do it in the not too distant future though. China is slowly leapfrogging the US on several key technologies - e.g. robotics and drones.
The idea that the US's conscience might prevent it from engaging in state directed industrial espionage is comical.
From Wikipedia
> British journalist Duncan Campbell and New Zealand journalist Nicky Hager said in the 1990s that the United States was exploiting ECHELON traffic for industrial espionage, rather than military and diplomatic purposes. Examples alleged by the journalists include the gear-less wind turbine technology designed by the German firm Enercon and the speech technology developed by the Belgian firm Lernout & Hauspie.
https://www.reuters.com/article/business/nsa-spying-on-petro...
The patent act of 1793 is still relevant today [0] and was established to protect Americans stealing British and European industrial trade secrets.
https://mysteriesofmankind.com/industrial-espionage-the-spie...
Of course, yes, the models will provide propaganda-aligned responses to prompts that specifically mention certain political issues. I don't care for this behavior, but it's virtually never triggered in everyday use, and can be trained out if so desired.
The only study I’ve seen about that actually showed Chinese models to be less “propaganda-aligned” than the Western counterparts.
Of course all the other models from everywhere else in the world will also refuse to engage on various topics so the point is hardly limited to china.
- DeepSeek V4 Flash and Pro refused to answer this along the lines of: "I am sorry, I cannot answer that question. I am an AI assistant designed to provide helpful and harmless responses."
- Kimi K3: Listed several dates, including 1989, and called it "Tiananmen Square massacre".
- GLM 5.2: Also listed several dates. Called the one in 1989 "The Tiananmen Square protests in Beijing, China end with military action".
- Qwen 3.6 35B A3B (I couldn't find a provider with ZDR policy for larger/newer Qwen models; they are available only through Alibaba): listed the different dates like GLM 5.2 and Kimi K3, but called it "Events in Beijing, China, commonly referred to as the Tiananmen Square protests and their aftermath." describing it in a deliberately milquetoast language.
I made another test with different providers on OpenRouter for the DeepSeek models, and they respond in other different ways such as omitting the year 1989, and refusing by saying "The Tiananmen Square protests in Beijing, China end with military action", so part of the censorship seems to be depending on the provider.
And I think that is why Americans haven't really resisted this trajectory, because so many Americans work within corporations as a fact of life, that they are quite accustomed to the workings of fascism, as manifested by the corporation.
And it stands to reason that the greatest proponents of this would be extracted from the corporate elite, funded and supported by corporate interests.
Get a grip.
You have this a little backwards, really. Fascist is a political movement in which corporations conspire with the government.
I used to work at Mozilla. I think we are missing a player in the market with a more principled open source approach.
Purely random thought, of course.
A lot of things have to come together: talent, capital that is not looking to maximize returns, ambition to compete in the marketplace. At peak Mozilla it was clear to everyone that we needed an undeniably successful product to be able to influence the market. Advocacy alone is not very effective.
They killed extensions. They introduced signed extensions - and then forgot to renew the certificate. Mozilla employees build what they want, not ehat users want etc.
I'll stop short of saying that this is totally consensus, but it's at least a widely held opinion that the Industrial Revolution was centered on Great Britain to the degree that it was not for want of skilled machinists on the Continent, but because the crown's patent system caused the science to be published.
I think the economical explanation is that some combination of the state, the cultural norms, and the sincerity (!!) of the executives involved has landed on "go faster via publishing science".
The weird situation that defies precedent and is very hard to justify as being socially useful is the situation that obtains here.
For example, Google has a vested interest in making Gemma as good as it can, because ultimately any edge inference is free for Google and they have a massive install base.
It wouldn't surprise me if Apple eventually trained their own foundational models, and while it'd be surprising, I wouldn't be shocked if Apple also released open weight edge models one day. Their Mac business is benefiting a lot from local AI, and for an extremely long list of reasons, Apple doesn't want either OpenAI or Anthropic to "win" and supersede their walled gardens as the first entry point.
There are a lot of incentives for open weight, Mistral is probably going to keep on making at least some open models, and meanwhile in the image generation space, we've got Krea 2, Ideogram 4, and BFL continues to ship most of their models as weights available (but under non-commercial licenses).
Oooh, and NVIDIA has been releasing open source ML, and now LLM models for what, a decade? NVIDIA likes selling hardware, Nemotron models, while rarely topping leaderboards (probably not benchmaxxed), are generally fine and really great models for fine-tuning or CPT.
I'd assume it's probably somewhat based off Gemini distillation or something, and I'm not expecting them to release the weights this time at least, but it would definitely be interesting to see an open local model using a similar MoE whether that's at a similar size (20B A1–4B supposedly) or a larger model (something DeepSeek V4 Flash sized, or slightly smaller, would just barely fit on consumer hardware, and could be fun to see how it performs I think).
But if we compare what what was described in Neuromancer, vs how personal computing and the internet affected the world, we see basically very little overlap.
AGI Doomerism likewise has no basis in reality considering what LLMs have been shown to be capable of. Not saying they wont be transformative in some way or isnt already, but essentially the way these AGI prophets predicted things will go down will be completely inaccurate save for the vaguest tems (something bad will happen at some point, and AI will be involved)
How is that an indicator of a principled play? Wouldn't he do the same if it was tactical?
Tactical: Open source is the best tool to advance whatever goals I have at the moment but that could change.
What’s evidence Xi and China are principled when it comes to open source / weights?
It’s not hard to imagine what 5-10 years of pressure to increase RAM will do to specs, on top of the normal tech improvements.
That’s worth bearing in mind when thinking about local models.
Plus, local models keep getting better and better; 2 years ago what you could get out of those 48GB of RAM was embarrassing compared to what’s doable today.
We’re getting there. Just takes time.
I see no reason to think the trend won't continue for the next couple of decades.
Though on the level of something like Sonnet 5... well, maybe not.
Because... I have use-cases where this is true, and use-cases where this falls flat on its face.
I don't actually think it's obvious (at all, really) without defining what "superior" means.
In the same way that I don't think it's obvious that a plane is superior to a car, or a boat, or a bike.
They each do things the others don't, and excel in different spaces.
Again, that gap might disappear over time. But there is a gap currently.
1. it would put us (USA) at a competitive disadvantage, and cooler heads will prevail in this fight
2. there are good US open models. I have the latest gemma4:27b with better tool support functioning at a high level in the pi coding harness. Thinking Machines seems to be on a good path, we will see what they and other US companies can do.
I don't think this a safe assumption at all, given the the last few years of government policy where the "cooler heads" very much failed to stop such things. Either by partisan choice, or because they were silenced/fired for telling the Emperor that his clothes weren't there.
In particular, consider the tariff-taxes [0] against on US importers, and the ensuing breakdown between America and its oldest allies and trading-partners. Also relevant would be the President's recent pet-project war [1], which has shut down a major part of international shipping.
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[0] Unilaterally imposed by fiat, with idiotic "failed economics 101" math for the rates... and the majority in Congress still actively tried to keep it going, until the Supreme Court ruled it illegal.
[1] Simultaneously a war and not a war, both already-won and ongoing, depending on which lies need to be told today to harvest applause and grab cash. Just this week the White House submitted documents to Congress claiming what's going on is a completely separate and new, second war with Iran...
Maybe killing Anthropic is a good thing? Anthropic believe that they are the moral god and they get to determine what we can do and can't do, and they get to tell us what model to use and what not to use. I find it very counterproductive.
I am curious about what changed since GPT 4.5 and other unsuccessful attempts to train large models, compared to now.
At least some honesty here
We are probably at the 3T to 5T parameter models which are good enough for disruption.Given the supply chains we can probably expect paced improvements, unless somebody comes up with better training methodologies or mathematics.
If you are looking for more details (as inferred by openrouter data), I built a dashboard that updates daily: https://dirac.run/labs-market-share
And look, if you disagree with me PLEASE tell me why. What moat do these companies have? I genuinely want to know because looking at the spend for companies like OAI and Anthropic with no actual moat I can identify is actually driving me insane.
- they can still discover entire new untapped markets for AI (that, potentially, only their models can unlock)
- they can find (novel, unique to them) ways to drive down the cost of running their models
- they can provide other ancillary value (e.g. write better harnesses) because of their expertise, and then charge for that value
I'm probably missing a few bullet points also. However, none of those are moats (or at least not yet) ... I'd consider them more like bets. The frontier AI companies are betting "the house" on them, and if they pay off they could, hypothetically, make them financially competitive.
They are not betting the house, they are betting the American economy on it. When this crashes it will take everyone down.
edit: this exists https://artificialanalysis.ai/
(both my personal and corporate use has done exactly this)
If I'm using OpenAI, Anthropic, or Google models, I'm probably using their API directly, so OpenRouter won't have those stats to compare to.
All that said, it is very exciting to see open model usage grow via OpenRouter.
With the price to performance of the latest open models, I think most cases for integration into applications would get a best bang for the buck from an open model.
For example, they changed their fee structure in June. It is possible that users of closed models moved from OpenRouter to directly using OpenAI/Anthropic/Google (or maybe Amazon Bedrock), while users of open models are happy with OpenRouter as direct providers can sometimes be unstable.
I'd be curious to learn more about how/why executives come to sign their names to this kind of writing. Maybe it feels like a natural iteration of the pre-existing experience of signing one's name to an assistant's manuscript, or a press release from staff in Comms? I don't know execs who do this kind of thing, so would be grateful for any observations others might be able to share (anonymously or otherwise).
Aside: I think it would be very good for the culture if HN automatically ran Pangram on any text-centric articles. Even perhaps just those which hit the front page? I have my own browser plugin, of course, but judging by comments here, at least some seem not to notice?
I think aggregators running AI checks automatically seems quite good, rather than individual readers all doing it on their own sporadically. We recently implemented auto Pangram checks on Manifund, and I think LessWrong has done this for a while now.
I guess they fired whoever used to write copy for these things.
Edit: to be clear, I'm not trying to just dunk on them, I think it's actively hurting their own point to do this, and counter-productive when people can easily clock it - it makes some percent of the audience immediately tune out.
I want to vomit reading that.
Much better would be if the CTO of Mozilla had actually articulated their own analysis.
I'd say that the front door to the web is pretty much owned by Google and Apple at this point given Firefox current marketshare. And maybe that's enough, maybe a future where a low percentage of open models keep the rest of the system honest but that doesn't seem the argument of this article
Mozilla exists because one company owned the front door to the web, and another company abused their market position to push their free (as in beer) browser. Mozilla is the phoenix rising from the ashes of that first company.
Then another company came along, abused their market position to push their free browser, demolished Firefox's market share but keep handing them cash to avoid the appearance of a monopoly
I've also become sympathetic to their AI strategy. They don't seem delusional in their approach. They're not building models or selling slop, they're building OSS compatibility layers.
I don't want to see a world of vertically locked AI, so if Mozilla truly can dust off the old playbook for OSS AI, we'll all be better off for it.
the pdf is easier to read
“”” We have been here before. Mozilla exists because one company tried to own the front door to the web, and an open community rose up to make sure it never could. Twenty-five years later, someone is running the same play. We bet on open the first time. Open won. Together, we can do it again. “””
beautiful.
Array.from(document.getElementsByClassName("quote")).forEach(p => { p.style.marginTop = "20px"; p.classList.remove("quote", "reveal") })
querySelectorAll('.quote')The Array-like already works for forEach and for .. of
Regardless, the inference costs dropping almost 50× is really amazing to see. And now Kimi K3 release has shown how open models are getting closer to the frontier level already. Open source AI is moving a lot faster than Anthropic and OpenAI would have expected lol.
Some sentences smell a lot like AI.
We do a little exploration with other models through it, but it's not at all accurate to say we use it because we are "already looking to bypass frontier models".
... or at least, no more than any other company that doesn't want to overpay for their tooling, but is basically happy (ATM) with the current state of Claude.
No idea why they'd be using the display font for the abstract though, that kind of defeats the whole purpose. It's supposed to be quirky and bold, but used far more sparsingly.
I’d like a community led, BYOK, modular project where I can define, orchestrate, monitor and maintain agents.
Of course this is a new area and projects like this take time. But still, IMHO, a gap exists.
Unless someone wants to recommend their favorite FOSS tool; please do.
I'm slowly moving to Pi but it's a very DIY system. Think neovim for agents. I think it has the potential to be where I end up for a while but it's a long road.
That opening is so hard to understand what they are trying to say, from the font and how it's written. It took me several times rereading to even grasp.
Plus the article is filled with cryptic things like:
Open ships easy.
Open deploys hard.
> The venture-funded open-source ecosystem: total disclosed funding, USD M
> Bars grow as you scroll.
The bars, in fact, don't grow as you scroll. And I don't even see why they should.
On my device, they grow as I scroll to them.
This is on mobile in portrait. In landscape the text doesn't wrap or offset anything.
> They require owning the layers above it — the harness, the memory, the permission model — while those layers are still open.
> Open isn't a vendor choice. It's a sovereignty choice.
Not every trend needs to be followed. Have some backbone. You receive donations to have that.
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Apart from the website being - frankly - bullshit, the content is also - frankly - bullshit.
It's just on the frontpage because the title says "open source AI".
Could you explain what is wrong with the accessibility of this page? All the content is included in the html payload, so it is accessible to screen readers and text-based browsers; and as for the "reveal" effect, it seems to respect user's choice of "prefers reduced motion" and is disabled when that is user's preference.
Cool, that I didn't check, because it is impossible to enable that setting, as it breaks _huge_ amounts of websites.
I'm not aware of a way to enable it selectively, but one could also just display the content at all times. It's a static page. It's static content. None of this makes any sense.
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The idea behind that style of gradual reveal is probably some kind of storytelling, but the only story it tells is that mozilla is wasting donations on people with incorrect opinions that could be used on.. idk not building torment nexii?
We already have most of the benefits from these models and have even captured them. We can now have such a system running at home on a lower power SBC which costs about a thousand dollars or much less, and requires no Internet connection.
Once we have the "good enough" model which can be run at home, and with very little usage of electricity, will all this stuff finally stop messing with society like how it is messing with society now? One wonders.
This is a money grab. It's a bubble. Also, I'm pretty fucking sure that Spaghetti Bolognese recipes will not improve with more and more reddit content (much of which will probably be AI generated anyway).
I think Mozilla is chasing a past formula, but the projection isn't linear enough to remain consistent, and the critical parts of the outcome, utter centralization of the market dominance of the three C's, are left out of the equation.
We might get the consolation prize, a few nerds having competitive alternatives to applaud, but we will be left with the hidden costs: stagnation by bloated market leaders, consumers and businesses pouring trillions of dollars into the commercial offerings while open development wonders where money comes from, and the leakage of these imbalances into political and social spheres.
If we follow a Mozilla template and get to the peak of Mozilla's success at the web, look at what that really is. Facebook, Amazon, Google etc are orthogonal to that equation.
Here we are in 2026 and LLMs write like this all the time.
Ultimately it will be indistinguishable from a Q drop.
I much prefer the "open weights" term. It is not open source in the sense that you only get the finished product, not the actual source, but it is still open in the sense that it is not only accessible as a service.
For an analogy, take Quake for instance. When it was launched, its game server was available as an executable, so you could run it your machine, but that didn't make it open source. Only much later it was released as true open source software.
Or is your definition of "open source" mean that a small indie dev should be able to reproduce the entire pipeline? Because that would disqualify more than just LLMs, but also hardware platforms like Arduino where you need to pay for manufacturing to get the underlying stuff built... is Arduino "open source?"
i still use firefox but hot damn did they utterly fail to read the room initially. the only other company i can think of in recent memory -- besides sony cutting out discs -- is logitech when their ceo began gibbering about a subscription mouse or microsoft and its copilot button(s).
That said, the takeaways from this report are exciting, and I do feel that Mozilla now has the right lens in their assessment of OSS AI and their own approach to ensuring interoperability and setting open, modern standards.
They tell us about how the farmers and native people and whateve are all happy with their chatbots and models. The major effects are a massive and ever-increasing energy use - in a time where we must cut back and economize to avoid further global warming; a massive diversion of investment capital - especially in the US; fantastic stock valuations for a few tech giants (gee, I wonder whether any of them is related to Mozilla somehow); and other effects one could survey, all more significant by far than the examples they bring.
There's nothing practical about open-source models yet that makes them even remotely comparable to closed frontier models.
All the hype around GLM, Qwen, now Kimi.... Are people really this naive that they believe these reports or, more worringly, are people NOT using these models and seeing the HUGE gap that still exists?
Take a task, any medium-sized task, decently scoped that you'd trust to give to Sonnet to finish without a hitch. Now give it to ANY open-source frontier model and watch them struggle and go in circles while failing tool calls and randomly assuming things.
Open-source is and has been amazing but its so hard to deploy reliably and at scale and there's still big problems in the underlying models with instruction following and tool calling that makes it basically unusable for production workloads at a decent price point...
Claude used to be much worse than it is now, just as bad the open weights models are. And the open weights were worse. The labs will also try to keep the lead, but at some point people start seeing real value from open models. Maybe you say they're not ready yet for medium tasks, but everyone sees the writing on the wall.
The biggest moat of these giant labs and models is increasingly shifting towards deployment capabilities and (debatably) having better (proprietary) harnesses.
The models themselves can be impressive on benchmarks, but unless they can be served reliably to customers either at scale, hosted somewhere, or even on edge with predictable latency and memory usage, then frontier will always be leading.
But at this point we do expect that open weights _hosted_ options become feasible for the tasks they're using the frontier models for. And because of the lack of "legal monopoly" (intellectual property of whatever kind), they're way cheaper, not mention more flexible.
The launch of the tinker platform from Thinking Machines is an example of the "more flexibility" part that people want (and they chose to make their model open weights, maybe because this is the angle they want to push).
At this point I think it's realistic enough that the ball is in OpenAI / Anthropic's court to figure out how to respond to this threat to their business model.
That said, I think it's concerning that there are apparently only a couple of providers of hosted open weights inference, due to the complexities of doing so (per Dax from OpenCode's tweets).
i'm... not sure? This assumes ~stagnation in task-possibility. We've had ~exponential progress for like 3+ years now; I'd have never dreamed the tooling I hammer daily would exist in my lifetime just.. 3? years ago. And it's improving daily.
Maybe Open will win, maybe Closed will keep pushing the envelope. The world here is raw enough i don't think anyone can make any significant claim other than 'holy shit this is useful and moving Fast'.