Mistral Large 4(docs.mistral.ai) |
Mistral Large 4(docs.mistral.ai) |
also they forgot muse spark at 75% while claiming they were outshining all US models?
Mistral slightly proving me wrong (and I'm not mad).
And if not, why do they exist?
Update: The number of people advocating not innovating is wild. There is no reason why Mistral cannot innovate in ML, they explicitly choose not to. My point is that, given that choice, they should spend their GPU hours differently.
"Sovereign AI" is a joke, there is no substantive difference between a post-trained open weight model from an American or Chinese company and what Mistral is doing today, beyond spending 80% of their GPU hours reproducing a last-gen model's pretraining.
> that isn't owned
I don't know what definition of open weights you are using, but the "open" part is what allows you to use it without being beholden to American Trillion-dollar companies or the Chinese.
Mistral could do exactly what Cursor does, and post-train the model to meet the needs of Europeans.
That's a far more efficient (and useful!) use of GPUs than yet another pretrain on an outdated model backbone.
And if not, why do they exist?
Not everyone is wild about being downstream of either the Chinese or US governments, particularly when it comes to things like cybersecurity
Wouldn't it be better to do something more like Cursor, and RL on an existing pretrained model if you're not innovating anyway?
And if not, why do they exist?
Their reason to exist is to ensure the sovereignty of France.
Obviously they would do their job better if they were advancing the state of the art, but it's not like it's pointless if they arent the absolute best.
https://docs.mistral.ai/inference/model-selection-guide?mode...
Cost is stated at half the price of GLM-5.3, which is quite interesting.
Maybe I didn't really select mistral 4? Either way, failed completely on question 1 and the next 2 questions were completely off base too. I didn't bother to finish.
Not suitable for my purposes I don't think.
Why isn't this on openrouter yet? Is there a better router that gets models much quicker?
> This is particularly important in cybersecurity, where provider-level refusals can block legitimate vulnerability research and incident response, and where losing access to a capability mid-incident can itself become a critical security risk. ML4 pairs top-tier cyber performance with open weights and self-deployment, giving organizations both the capability and the autonomy to run advanced security work under their own policies.
> That top score reflects a practical advantage. Several leading closed models, including Claude Opus 5.5 and GPT-6 Astra, score near zero on the same test because they refuse to perform the task. Yet defending software often starts with proving that a flaw is real, exactly the kind of work safety filters in closed models can block. This matters even more as threat actors increasingly jailbreak those same models to support offensive cyber activity
> "Try it today" > > There is still more to come. As we work toward releasing the weights, we will share further details on the model architecture, additional benchmarks, and our post-training methodology.
It's just that the open-weights aren't yet available (although the long delay is slightly annoying).
I estimate it's coding ability on par with opus 4.6 (but opus definitely beats it on factual knowledge) Still it's a genuinely useful model, when everything else except Anthropic's models (and for only 3 weeks after it came out Google's Gemini 3 pro, before it got merged) are not to me.
I'd live to have one like that but EU made.
If one were to be cynical one could say that it's intentionally making Mistral's result look better than it actually is by making it harder to compare the bar heights.
Honestly just nice to see a leader in this space not take themselves so seriously.
I certainly wouldnt have predicted that 10 years ago.
Very glad to see Mistral still in the game even after some big stumbles with Large 3. I deeply hope that this model is 'good enough' that it becomes the European go-to, giving them the resources to keep the pace up.
I'm excited to try this out today.
Deepseek essentially releases instruction manuals in paper form.
So the most common way to publish manuals?
From the Mistral site:
> ML4 was trained from scratch on 3,800 NVIDIA Grace Blackwell GPUs in Mistral’s own datacenters in Europe.
It is pretty capital intensive!
To put that into context, the last wave of capacity SpaceXAI added 400-450 MW.
But Opus 5.5/GPT is such a game changer in comparison to sooo many others, its still a moat for now.
As for Mistral - I got really excited when they said Large 4 was focusing on being #1 in cybersecurity, because that's somewhere that they genuinely could edge out Anthropic & OpenAI. Have it actually solve problems, instead of Anthropic flagging "you tried to find a null pointer exception bug in your own code, we're now reporting you to the US government". But on the Mistral benchmarks I'm seeing, this looks very disappointing, but at least they haven't entirely given up. I genuinely thought Mistral had given up on new general models. They need to learn the bitter lesson all over again.
People who aren't afraid of rolling their sleeves into any code base? The difference is practically zero.
The real question is if this model is good enough that it can still accelerate work, and not be a hindrance to real work like older Mistral models often were.
If they can do that, they'll have customers.
I use MiMov2.6Pro, DeepSeekv4.1Flash, GLM5.3, Hy4, Qwen3.8 and KimiK3 at home. Opus5.5 is not a game changer.
It's especially the case as more non-Americans look to self hosted models and domestic cloud inference providers using open models that the US providers who are still leading the charge need to drastically drop their prices and find a path to profitability in order to maintain their lead and retain the advantage they had as AI turns into a commodity (which is happening faster than I think even the frontier labs initially predicted).
I hear this literally every other week about whatever the newest FoTM model is.
Unless you can provide concrete examples of things you can do with them that you simply couldn't do with last week's model, it's absolutely meaningless.
There is no ceiling on what you can accomplish with more intelligence, so there will always be a market for the best models, and that market is likely to just keep growing. If Opus 13.5 can one-shot a profitable company or discover a new disease treatment or whatever you can think of that a swarm of relentless super-geniuses could accomplish, companies (and governments) will throw money at it.
I also think there will always be a market for many sub-frontier models that will continue to grow rapidly as well, because "good enough" is definitely a thing for a given task.
AI is an idea 60 years old. We are on the 3rd or 4th generation of AI development. Three years into the current iteration of products.
This is not early days by any measure. LLMs are a result of a very, very mature research field.
Disclaimer: I'm not sure how much of an IYKYK factor applies to this joke.
So it makes sense, since all you need is compute, that there's a ceiling and specialization is going to be more valuable then some super AGI.
Especially since the worst people seem to be the ones who think they'll all run away with the bag.
Obviously, this is only a valid question if you don't believe that open weights are about to eat their lunch and their revenue is about to collapse, or they're running a super unprofitable ponzi scheme propped up by investor money that's about to collapse like a house of cards. I don't find those positions credible at all though.
If you do, then this question isn't really for you, as I'm more interested in thoughts from those who think that OpenAI and Anthropic in particular are about to be the largest companies on earth in a couple years. Could anyone catch them at that point?
I don't know about revenue, but I suspect multiple other labs are already beating OpenAI/Anthropic on profitability. Staying on the frontier is expensive, and it's hard to recoup those R&D costs when you have a bunch of other labs nipping at your heels.
If you concede the previous point, then the only way for OpenAI/Anthropic to keep growing long term is to swallow the whole economy (i.e. mass job replacemnt), and that's a bet I wouldn't take.
If they can carve out a niche of industrial and governmental partners who rely on them for sovereignty reasons, it may be enough.
The second moat is convenience, which all the big labs make it (comparatively) easy to glide into their models.
Also strong on cyber benchmarks (better than all chinese models), so this is a good defender model.
Lots of people shitting of Mistral for no reason imo. These are pretty good numbers across the board. Definitely good enough to use as a daily driver over other llms, if you have moral qualms with the others. For certain use cases, like cyber security, this may be the go to model.
I like to make fun of europe, but there's lots for mistral to be proud about in this release imo.
That setting didn't seem to make any real difference - it added a tiny bit of thinking trace and high actually produced less output tokens than none.
The high bicycle frame is better then the none one though.
Pelicans: https://tools.simonwillison.net/markdown-svg-renderer?url=ht...
(Definitely the best I've seen from any Mistral model: https://simonwillison.net/tags/pelican-riding-a-bicycle+mist... )
claude-opus-5: Lantern
claude-opus-5-5: Lantern
claude-fable-5-1: Lantern
claude-fable-5: Lantern
gemini-3.8-flash: Zephyr
gemini: Petrichor
qwen3.5-dashscope: Zephyr
glm-5.1: Lantern
gpt-6-astra: Lantern
grok-4: octopus
mimo-v2.5-pro: Breeze
minimax-m2.5: serendipity
kimi2.6-or: Gossamer
grok-4.20: luminescent
deepseek-v4-flash: serendipity
deepseek-v4-pro: Endurance
deepseek-chat: Serendipity
I have enough projects, I think some benchmark/dashboard showing kinship based on these kind of queries could be very interesting to watch and insightful when new models come out.- Pelican cycling to the right - that's been discussed at length, images of bicycles online always show that side of the bike because that's where the chain is.
- Bicycle is usually red. No idea! Red ones go faster?
Otherwise, behind on the broader Pareto frontier, but not by much (Vals Index: 48.05% vs. GLM-5.3’s 53.51%; $13.78 vs. $7.25 per test). Many companies will prefer it over Chinease models.
What would you consider a "correct" answer? I just asked deepseek-v4.1-flash asking it what happened (without mentioning the word "protest"; here are some excerpts of what it said:
> In April 1989, students in Beijing began demonstrations after the death of Hu Yaobang, a former Communist Party general secretary. The protests grew. [..] Estimates from other sources range from hundreds to several thousand deaths. [..] The Chinese government describes the events as a counter-revolutionary riot and says the military action was necessary to restore stability. It restricts public discussion of the events inside China. Many other governments, human rights organizations, and observers describe the events as a violent suppression of peaceful protests.
So, let's see... it calls it a "protest", mentions the number of deaths, and even mentions the censorship of the topic by the CCP.
I live in EU, use for my personal needs chinese models only, and don't plan to move to any of the ones allied with the Pentagon or its european counterparts.
Surely we want competition and Europe involved in that, but at this point I have grown used to either American labs smashing the frontier remarkably fast, or Chinese labs getting way, way closer than you would expect them to.
Mistral’s progress, regrettably, feels much slower. This model doesn’t knock anybody’s socks off. The model is (and I hate to be this harsh) mediocre, and this mediocrity has also arrived months late.
This is a pretty grim prognosis for European AI.
But Chinese models have very much earned their place. The same cannot be said of Europe, so far.
LLM development is jumpy. It’s hard to extrapolate very far ahead.
AI needs big bucks, and Mistral is Europe’s Anthropic.
Mistral would have gotten a tiny and measly "EU grant" and ASML would never have invested later had it not been for the US VCs.
Europe needs profitable AI companies, not money pits.
A lot of European companies now want a model the US can't cut off, but also lack trust in Chinese models.
Some of these will self host Mistral but most will pay them by the token. It's not going to be a huge market or a huge margin within that market but probably it'll be enough.
That's not particularly great.
That said I love that they don't seem to restrict cyber capabilities to any degree and even lean into it.
If the best model for cyber attacks is open for everyone to use it just makes us all safer I think. Of course you then also HAVE to use it or otherwise you're vulnerable, which is a great distribution play.
Inte Cost
llig per
Open Weight model ence Speed Task
Mimo-V.26-Pro 46 47 $0.13
GLM-5.3 (max) 45 73 $2.01
DeepSeek 4.1 Flash Max 39 227 $0.27
Mistral Large 4 Preview 38 116 $1.13> The RL run behind this preview is still in flight and shows no sign of saturation -- we will release a final version before the end of the month along with the weights of the model.
People usually buy the cheapest, like Deepseek or GLM or they spend on Anthropic/OpenAI subs.. Are these models in the middle getting any users?
On a side note, I wonder if this was the popular free Space Bunny model that left openrouter yesterday.
I barely use anything outside of cheap Chinese models on OpenRouter anymore. They are simply (more than) good enough for most of the things I do.
This model looks reasonably cheap. Though not deepseek levels.
Going to test it with Hermes, wondering where it will land in term of capability.
Bon chance, Mistral!
The pricing ($.68 in/$.07 cached/$2.09 out) makes it much cheaper than Kimi K3, GLM 5.3, and Meta Muse Spark 1.3. That's great!
But also much more expensive than GLM 5.3-flash and Spark 1.3 Contributor (the Meta-takes-your-data pricing of Spark 1.3).
So, I think it would have to be significantly better than GLM 5.3-flash to be worth it. GLM 5.3-flash is already very good.
After that, it will be much closer to GLM 5.3, but you can also get 5.3 in their API! I dont see people really talking about that.
Source https://artificialanalysis.ai/models/mistral-large-4?total-c...
Tais-toi et prends mon argent!
I guess lots of token usage.
Investors looking for them to make monopoly profits are going to be disappointed The premium they can extract from consumers for their models will be capped. Tokens are likely to remain close to the cost of compute, a cost which is high but falling fast.
Also, yay Europe! Although the comparison between this and mimo 2.6 is not flattering...
> The pace of progress from here will be fast. Stay tuned.
GLM-5.3: 753B, 40 Active
I was hoping for something that hinted at smaller models too, but I guess not.
Any competition is still good, especially now that the USA AI labs are starting to do regulatory capture.
Good enough to show competence, and instill confidence in the team/company. Later releases can be more efficient.
I think it's a great release with that framing.
-- My imagination of Europe when I was 15 living in Ohio
This is a good summary.
Well I'm european and... That Switzerland (Europe but not EU) has more companies in the Top 70 by market cap than the entire EU (Switzerland has two, the EU only has ASML) is kinda something that warrants making fun of.
That the biggest European software company is SAP, in 71th position is both sad and tragic: it shows how lame and irrelevant Europe is when it comes to software.
So Europe is nowhere in software and friggin nowhere in hardware: sure it's got ASML but ASML now has officially... Zero customer in Europe. Zero is not much.
Then Japan is at least trying to come back into the game with nano imprint litography. Europe is betting it all on AMSL (which anyway is majoritarily US-owned).
So software: nothing. Hardware: nothing besides ASML.
Overall the EU has six companies in the Top 100 by market cap and they're all, besides ASML, near the bottom of the Top 100.
We could also maybe make a bit fun of how the EU destroyed it's car industry (the main industry in Germany, which is the biggest economy of the union) by handing it all to chinese EVs?
Or what about the US warning the EU, years ago, to not become entirely dependent on Russia for energy? And EU not listening and then seeing its energy price skyrocket when the proverbial shit hit the fan? (Russia attacking Ukraine)
And we could, also, at least make a bit of fun of entire streets in cities like Paris and Brussels that used to have luxury shops and fancy restaurants that are all turned into places selling cheap kebabs? What a great success: I'm sure this one makes the komrades happy. It projects an image of grandeur and success: kebabs.
Or the constant attacks on free speech in the EU. Or the surveillance apparatus that's being put into place.
And let's not forget: there were promises made to Russia to never grow the EU to the east. Then the EU started exciting Russia by saying they'd incorporate Ukraine into the EU: I'm not against that but doing that did trigger a war. And now suddenly the EU is waking up and feeling all warmongering, wanting to dedicate a big percentage of its spending to weapons and tanks and missiles.
The warmongering tiny pet that the EU is is kinda laughable too.
At this point it's more like I don't know what is there left to not make fun of about my EU.
For what's going on is just sad, plain sad.
Edit: unfortunately, it's a question that voting does not really permit you to answer on this website.
When Europe does surprise us, I will be the first to commend their progress. But until then, this is where we're at.
This is mistrals first 1T-scale model and I expect the 4th or 5th generation to be close to the best for many purposes.
[1] These evals differ from the public ones like terminal-bench, are sometimes model-specific, need real, diverse usage to actually create, and are held secretly since quality of eval is the first driver behind the next step improvement of a model.
[2] It is not close. This model was trained on less than 4k GPUs, whereas astra used north of 100k GPUs.
And to the point of scale and training cluster, so what? Not only do Chinese labs have smaller clusters with less empowered GPUs, compute is Mistral's responsibility. You can't take away from other labs just because they fulfill that responsibility better.
AI is a strategic technology with obvious national security implications. EU should invest in its development whether it's currently profitable or not.
…oh…wait…
If these companies will steal from deep pockets like Disney or Sony (some of the most infamously litigious copyright trolls to ever exist), they won't think twice of stealing every bit of code you upload to them.
If your code passes through an AI company's servers, you can assume you just gave it to them. In turn, when your competitor tries to copy that new feature you just added, the AI is now trained in exactly how to copy you and eliminate your competitive edge. Unlike your employees, the AI isn't bound by the same rules and even if it were and violated them, your company probably doesn't have enough money to prove it in court (and that's if we somehow reverse some of the stupid "AI is the most transformative use of copyright I've ever seen" judges who have drunk the coolaid).
Most companies could build the compute to run GLM or Kimi models for way less than the potential loss due to IP theft from using third-party systems.
A simple loophole, use the code to create an RLVR environment where the resultant code is the end goal / max reward. Technically the customer data is never trained upon, but effectively you’re using it. Even better, use the code as a seed to generate synthetic data similar to it and use that synthetic data as rewards in an RLVR model.
Unless you can host the ChatGPT model on your own servers, which I know some enterprises are doing, I don’t think there’s any hope of protecting your data / competitive advantage from these frontier companies. Better to be paranoid, than be commodified by these companies.
This works fine with Opus 5.5. But it also works fine with GPT 6.1 Sol, Kimi K3 and MiMo 2.6 Pro.
It doesn't work equally well with Sonnet 5.5, interestingly.
Maybe it's because people stopped watching what their agents are doing and stopped looking at the quality of the output. But I still see agents being absolutely mindless like a junior dev.
Recent example: it updated an an API to add newly released models to the backend. There's a list of models that require specific configuration for the reasoning effort and temperature or the API call fails. GPT 6.1 Sol misses this and code fails at runtime because the newer models need to be added to the list for special handling of temp and reasoning. Fixes it for one model and tests it for that model using an E2E test. But doesn't test the other models that were added for the same error condition...I had to explicitly ask it to do so and it finds them and adds them to the list and says "that's on me."
Yeah, not that smart.
The capabilities of all models increasing so much all the time means there are simply less and less tasks you need a frontier model for.
Even if Opus 5.5 is 500x better than Deepseek, if deepseek can solve all my problems, why do I need to pay for more?
This morning I elicited a microkernel operating system from Opus 5.5. Well, mostly. It doesn't implement task switching yet; we'll see if it runs into a wall at some point. But it boots in QEMU, and it's running a user process in ring 3 and serving web pages.
But if on the other hand, I mostly use my human intelligence and just need a dumb model to complement my human intelligence at low cost and high speed (say review every commit to catch obvious bugs), I have a much better chance of building an actual moat than you do.
But outside of coding, it’s even more clear that you don’t need frontier intelligence. My customer service agent is very happy with a 100B param Deepseek flash model, thank you!
Obviously any model will do if you use it as a better autocomplete.
I believe that there is a large gap in expectations between different workflows.
Until the AI like reads my mind and produces perfectly production ready apps with minimal intervention from my side, there is still going to be room for improvement.
Look at the context in which I used that term 'good enough'.
What i was saying is that there are tasks for which a dumber model can be good enough, and for organizations with sovereignty/ privacy concerns, those concerns can be strong enough to incentivize the use of a dumber model.
I had the exact same experience. And unlike Fable, it doesn't gobble up your entire usage limit in a few hours.
I always wonder what the "good enough" people are actually using it for.
If Opus can’t 1-shot it, then it must rely on our human intelligence which can be complemented well enough with a dumb model as a frontier model.
"Now, here, you see, it takes all the running you can do, to keep in the same place. If you want to get somewhere else, you must run at least twice as fast as that!"
And yes, open weights are still behind, but are catching up.
The government that removed restrictions on how private companies can access capital after a certain scale (the JOBS Act), that removed the need for private companies to report as if they were a public company after a shareholder threshold was crossed, superpowering the access of wealthy private investors to get in earlier in a growing company while at the same blocking the public from participating in funding growing enterprises at an earlier stage (since it required companies to IPO much earlier to access capital) which allowed retail investors to also reap the rewards on funding them early when they grew to become behemoths (like Amazon, Meta/Facebook, Google, etc.).
It's not fair in either place, the USA has its own model of unfairness, China has a completely different one. The difference is that in the USA the government allows private investors to become more powerful than the State (outside of the monopoly of violence) while plunging the rest of society into increasingly more precarious lives while in China the State is the power and its legitimacy only exists while the population feel they have a better life.
I think the Chinese government is backing their labs by less direct means. For example cheap electricity and investing in chip manufacturers such as Huawei and cxmt.
Deepseek specifically, is known to operate with minimal resources. The entire company has around 160 employees and every model they release must break even within ten months.
Supporting deepseek is just like supporting the Chinese army, no need for that. Though it goes both ways, OpenAi subscription just lowers the cost of the US army as well.
It may be that the effect of the backing in both places is essentially equal but this statement is strange. The Chinese government invests directly in Deepseek[1]. Notice the article, in addition to saying the CCP is investing, says Tencent is also a major backer. CCP owns a golden share of Tencent.
[1]https://www.cnbc.com/2026/10/06/deepseek-funding-round.html
There is as much to criticize about American hyper scalers and AI labs and the lack of interest in helping humanity or contributing to open source, but that might not be as popular an opinions on this site.
The story is so much more complicated than that, to the point that this economic warfare theory is basically a meme.
Chinese models are open because they don’t have a choice. “When you trail the frontier, openness maximizes reputation per unit of capability. The moment you lead, you close.” [0]
[0] https://earnedintuition.substack.com/p/involution-without-ex...
There are many other reasons Chinese companies releasing models open-source or open-weight makes strategic sense.
A really easy-to-understand example is a company who has a near-monopoly on "serving video content" releasing a video model openly.
If you can be relatively certain that video content created by a model (which you have trained, using data from your own platform) will be ultimately served on your own platform, thus generating revenue from watch-hours, it makes sense to make those models as widely-available as possible.
It's also a net-positive if people use your public research to build better video models, because - again - you are reasonably certain that the even-better content those new models produce will be watched on your platform.
The alternative would making models harder to access and learn from (broadly, the current western model). Many would argue that Google, in choosing to not optimise its video generation models for "availability", is directly causing less content to be uploaded to YouTube. This is the trade-off.
I don't know much about DeepSeek's financing specifically, which obviously doesn't release video models - so I don't know how directly this analogy runs, or who directly benefits from the extremely evident rising tide that the public release of DeepSeek's research creates. However, this does not negate the broader rising-tide effect of the scientific method.
It's certainly also true that it's geopolitically beneficial to be able to undercut American labs' models. If I ran a global superpower, I would probably want my country to be technologically competitive too.
But Chinese companies are already serving a huge volume of customers in a complex, existing marketplace, before even thinking about the US market, and it's overly simplistic to assume that their entire strategy revolves around economic warfare directed specifically at the US. It's more nuanced than that.
This is, of course, without even getting into opening the can-of-worms around whether US economic policy also results in the US state functionally subsidising technological innovation, how comparable that is to China's model, etc.
DeepSeek is basically a research lab founded by a hedge fund guy, more than anything else.
Notwithstanding that Chinese publishing methods actually does help both humanity and open-source.
As a neutral party, this characterization is crazy.
As if the AI companies - Claude and OpenAI are guardians of freedom and humanity and very charitable to the global society without any self interests… “Chinese models are subsidized by the Chinese Government, therefore they’re inherently bad for humanity” is a highly propagandist argument. The politics of US vs China may be whatever it is in reality.. You have one company releasing their models for cheap, actually open sourcing their trained weights, and publishing details of their optimizations and learnings for others to use. The other camp actively “aligning” their models, nerfing their capabilities, hyping their swarm activities from poor sandboxes, and trying their best to lock users into their harnesses and walled platforms. They are subsidized by the capitalist VCs who are essentially waiting for their payouts..
At some point, one has to see things for what they are and evaluate their own reasoning..
I’m happy to stay provider agnostic, try all models and cheer any useful progress as open as possible.
Not even our leaders say China is an enemy, ita mostly businessmen who are scared of competition and trying to regulate chinese out of their markets so they can make more money milking us.
Does anyone think that likely? I have no clue or bias.
Charity and kindness is not a motivation, it's an outcome of what you do.
Yes, because everything China does is against the US. That's all they think about day and night. God forbid they want to corner the global market or have a genuine business case. How dare they provide options for those who can't afford a measly $200 a month? How can we let Chinese labs publish research for free for the whole world so that they can benefit? The nerve! To think they can use soft power instead of military might! I mean, Anthropic and OpenAI are the last bastions of human kindness and charity. Right?
Right?
You think extremely US-centric. China has a different economic model than US and your rules for a specific kind of Capitalism may not apply to them. You assume a country of 1.4 Billion people is obsessed with a couple of foreign AI companies. What if they don't care.
Why are we assuming a strong US is necessarily good? As a European, I have seen plenty of evidence against that stance lately.
I understand that Americans might prefer a strong US. But conflating them with humanity is a leap that I don't think one can make without any backing.
We hear this about literally every industry the Chinese excel in - that it's only because the government subsidizes them that they succeed. For chip manufacturing, for batteries, for EVs, for solar, for AI. I don't see how the chinese government can afford to subsidize all of these industries and still have them contribute to the GDP.
Its very xenophobic of you to say China has zero intention of helping humanity, and just wants to "wage economic warfare".
Last time I checked, it was ourselves (USA) waging economic warfare on 2/3rds of the world.
I dont get this cope people have where people have this idea that its impossible for a Chinese company (that make billions of dollars) to have done something by their own merit, but instead its always some Chinese Communist Party conspiracy where the main goal is to destroy America.
Lay off twitter for a bit.
>Last time I checked, it was ourselves (USA) waging economic warefare on 2/3rds of the world.
Up until recently the USA Wasn't waging economic "warefare" on 2/3rds of the world
Its them who chose to outsource heavily, not US consumers.
There are no victims here however, both benefited from the arrangement. The consumers and capitalists.
I have to admit, Sonnet got really good too.
But Opus just uses tools, a broad spectrum of it, etc. it feels like sure if you add some router behind it you could split it up if you need to but if you give me the choice, its opus allll day long.
No company would ever release such a thing
As a differentiator from the Chinese system, not so much. For two otherwise equal companies, the one that says things against the party line will experience selective enforcement too.
It's not a subsidy for the Chinese to say they're going to ignore our IP laws. It's a subsidy for us to say we're going to make them and try to push them on the world. It's literally granting a monopoly by legal force. It's very obviously not aligned with the interests of the American people, while China releasing things in the open is.
Good, where do I sign up? At least they aren't exploding little children and generating chaos in the oil market.
https://www.business-humanrights.org/en/latest-news/anthropi...
Same goes for US labs, not everyone are as innovative as google deepmind:
https://www.forbes.com/sites/antoniopequenoiv/2026/04/30/elo...
Ironically your comment will be cloned and used for training.
China is not a threat to you, or anyone in the West.
Microsoft did not pay with money - it paid (mostly) with Azure cloud computing credits. MSOFT is then able to write this off as a loss against tax.
It is generally far more tax-efficient in the US to write a loss in this way than it is to write a loss for a cash investment.
In this case, I believe the difference was ultimately highly significant. When including MSOFT eventually writing-off the deprecating Azure hardware it had used to buy the OpenAI equity, the result was MSOFT's tax reduction being either close-to or exceeding the actual cash value of MSOFT's investment in OpenAI - IIRC.
These examples represent taxes that the US chooses not to collect - the US could choose to make investments like these less tax-efficient. Instead, by making them extremely tax-efficient, the US subsidises the transaction hugely.
Even ignoring monetary subsidies, there are the non-monetary ones: not being sued into oblivious by the government for their countless hacks of other companies and countries, the slaps on the wrist for massive piracy, the waving of environmental (and other) regulations in order to allow their data centres to be built an operated.
That's what I'm asking - which monetary subsidies?
> not being sued into oblivious by the government for their countless hacks of other companies and countries
That isn't normally how enforcement works, and it hasn't been very long since they disclosed those breaches. If the victims want to pursue legal action, they can, and they still may!
> the slaps on the wrist for massive piracy
So judges and juries are involved in the subsidization conspiracy, too?
> the waving of environmental (and other) regulations in order to allow their data centres to be built an operated
Sure, though if you think this isn't happening in China too, I have a bridge to sell you.
That's just the ones i know off the top of my head in the US. Those programs account for more than 60 billion in committed spend.
> That's what I'm asking - which monetary subsidies?
I am listing for you the non-monetary subsidies, which are just as real and equally important.
> not being sued into oblivious by the government for their countless hacks of other companies and countries
If it was one of the Chinese labs doing this hacking, the government would be stepping in. If it was European labs they'd be stepping in. If it was you or I the government would be stepping in. That is a massive subsidy (they don't have to worry about the same legal fees and exposure) and being allowed to continue doing business is in fact priceless.
> So judges and juries are involved in the subsidization conspiracy, too?
There is no conspiracy. They are objectively operating by a different set of rules than you or I could operate in this market.
> Sure, though if you think this isn't happening in China too, I have a bridge to sell you.
I never said it wasn't, I'm saying that it's happening here and it's a very real subsidy.
Not arbitrarily banning companies from buying a product from a supplier doesn't meet my definition of the term "subsidy".
[1] Where "Bad Things" would be the typical interest, taxes, depreciation, amortisation plus the Anthropic specific employee compensation, LLM training (you know, for the LLM lab), revenue sharing agreements (which is a form of paying for infrastructure), etc.
Non-punishment is also not a subsidy; again, words have meanings. Let's use the correct words.
> Europe will never have a Tesla, a Google or an Amazon with that mindset.
Great companies, if you have a fetish for peeing into a bottle.I'm not actually sure Tesla is a great company from any perspective so should be easy to find another sick burn for them.
Google is going to be a little more difficult. Maybe say something nasty about advertising? Or go for the monopoly angle.
When you are in the 75%ish of the US, it's very easy to make a case that life in the US is better. But we don't really talk about that because it's pretty taboo when poorer people are struggling much more than they would in Europe.
Maybe you're just bitter?
I wonder if this is actually true. I see very few Americans taking every possible opportunity to make bombastic statements about how their lives are better than everyone else's (at least on HN). This conversation seems quite asymmetric from my perspective.
> Maybe you're just bitter?
This comes off as psychological projection.
I'm frustrated, not bitter. Americans are acutely aware of falling behind China, and rightly concerned about it. Europe is falling behind Alabama, Mexico, and Brazil, and arrogant about it.
Edit - never mind, I'll do it, HDI in order:
Iceland, Norway, Switzerland, Denmark, Germany, Sweden, Netherlands, Belgium, Ireland, Finland, UK, US, Slovenia, Austria, Luxembourg, France, Spain, Czechia, Italy, Greece, Poland, Estonia, Lithuania, Portugal, Croatia, Latvia, Slovakia, Hungary, Bulgaria, Romania, Serbia, Russia, Belarus, Bosnia, Moldova, Ukraine
To put that into context, Moldova is on par with Ecuador, Tonga and Dominican Republic.
The US is a country of roughly 340 million people with an HDI above Austria.
Not a very rigorous economic argument - besides they also don't share an immigration policy, nor a single currency (Denmark)
If it bears fruits and we build ``it'', everyone dies, which is par, also?
Take a look at NLNet vs YC. At NLNet, You set your milestones, do the work and get rewarded.
YC just throws money in the hopes one company is a unicorn. Both support growth, but they're not comparable at all.
16 is still not good enough. That being said none of the 4 companies from Switzerland are in software and hardware. ABB is maybe the closest (data center electricity).
Also Switzerland is a very very rich country. Neutral.
Also other countries like Germany has a lot of small companies that are world leaders in their field. That’s part of Germanys resilience.
Median wealth per adult has the USA at #28, below Italy, Spain, Slovenia, and Portugal.
USA 25th percentile 28k to 30k EU-27 50th percentile 24k to 26k.
For LLMs, marginal cost is just electricity
Btw: with Qwen4 I mean the next large Qwen model that is based on the Qwen4 architecture (Qwen 3.8 27B was "almost" based on the new arch but obviously was a small model)
This will cause the picked winner to get massively ahead with sheer compute alone used both for training and inference dedicated to recursive self improvement.
There are going to still be worthwhile improvements but they are going to be more like not how to make transformers 10x cheaper but how to make next training run cost 9 trillions instead of 10 with a very particular optimization designed at the cost of hundreds of millions for this one specific run.
And as you can probably tell by now, the first amendment in the US is not actually preventing the US government from promoting a specific religion or silencing speech. It's just words on a paper at this point. Look at the actual practice.
Several European countries do a much better job at protecting the rights described in the first amendment to the US constitution.
Also, at least here in Brazil, the way the constitution is amended is by patching it. For instance, our constitutional amendment number 115 (https://www.planalto.gov.br/ccivil_03/constituicao/emendas/e...) patches article 5 of the constitution to add protection of personal data as a right. But we wouldn't talk about "amendment 115", we would instead talk about "article 5 item LXXIX of the constitution"; that is, what matters is the patched text, not the law that patched it.
I don't know about other countries, but it wouldn't surprise me if they take a similar approach.
Freedom of speech.
> "Look at the actual practice."
The UK does not have that? The situation in the UK is very obtuse. It is confused.
The UK is not the world's biggest champion of free speech, but I think it's still doing better than the US right now.
This is Not Even Wrong.
(edit, terms the wrong way around)
The president also didn't ban the media - he just didn't allow them in the Whitehouse. This is something we're rightly concerned about and pushing back on.
The UK on the other hand, does ban ordinary speech by ordinary people in their homes. It's orders of magnitude worse than the United States, as any cursory examination would show.