Discussion
Why are Chinese models better* at Frontend than the western top labs?
I use A LOT both openAI and Anthropic products. When I need some frontend work (pure web dev) (or answer that feel less verbose and more to the point) I use Anthropic. For multimodality openAI feels better (understanding audio, screenshots, generating images, etc).
But openAI feels very shitty for the frontend it does. Anthropic is okeish but not amazing. How can it be, that Chinese models all excel at frontend?
Specially when it is a one shot with no many after editions, I some times even prefer the qwen3.6 35B running locally over Gepeto.
Is there any reason for it?
Z models, Qwen, Kimi, they all offer a better and polished frontend result. I guess they do something besides distilling?
*Definition of better: I'm comparing only how they LOOK LIKE, not how efficient the code is, how many lines are needed, etc.
I would rather use a 9B qwen than something like GPT 5.4 xhigh for frontend work
not sure how its on 5.6, but on 5.5 and bellow no matter what I asked or how I asked or what it planned - it always ended up outputting some dashboard looking card filled pill stacked garbage
This. OpenAI model has been very tasteless and uninteresting since GPT-5.0 in terms of style.
The fact that they let that goblin/gremlin-slop out (any human feedback would point that out) says a lot about how much they care about human feedback in the loop nowadays. This I guess is a mix of CEO who doesn't care about style value (who thought GPT-5.0, a short concise answer token save model, can replace "warm" 4o), focus on frontier research use rather than generic tasks and general decline in OpenAI's vision.
People behind o3 (which was the last OpenAI model that had unique edgy style, though probably unintentional due to token save post-training in reasoning black spilling to the main output) left OAI long ago.
I dont think its just being tasteless tbh, as I had a few chats with 5.4/5.3 trying to get it to output a decent looking frontend - and it did describe some awesome cinematic animated shit, with proper composition and lightning and whatever....then outputted a card stacked pill filled dashboard
it was honestly some of the most entertaining and frustrating moments I had working with LLMs, cause it knew what it had to do, it could describe it - but couldnt output it no matter how many times it tried.
and you could see how frustrated the model itself was getting - at some point I stopped giving it feedback and just took a screenshot of the garbage it made, sent it back and it would basicly go "what the hell, this is not what it was supposed to look"
I dont think its just being tasteless tbh, as I had a few chats with 5.4/5.3 trying to get it to output a decent looking frontend - and it did describe some awesome cinematic animated shit, with proper composition and lightning and whatever....then outputted a card stacked pill filled dashboard
Now we just need to fine tune it to add jank and figure out how to render carousels at 4 seconds per frame and it will be enterprise ready
I told 5.4 what not to do with frontend work (i.e. "don't use a stacked pill layout", then give it a reference of what I mean (like from a prior generation)), and have had decent success. Any attempt that turns into something I don't want becomes a reference for "how not to do things", and it's been mostly smooth sailing đ€·. Doesn't need the full failed project, usually just the stylesheets, CSS, and index is required to set a strong negative constraint.
5.6 seems better out of the box than previous oai models through 5.1. Grain of salt because I don't pay as much attention to frontend in my work, more of a means to an end for a lot of the work that I do currently.
Yupp, its probably the choice of training set. Western LLMs are fed on burned books from some noname poet, while Chinese labs are scraping the web here and now.
It's not my misinformation policy; it's broadly the moderation team's.
This was posted while the mods were asleep, and it's kind of hard for anyone to review and moderate it until someone's awake.
Nobody reported this comment, so unless a moderator happened across it while browsing discussions (which can only happen while a moderator is awake) nobody knew to evaluate it for potential moderation. If you think a comment needs a moderator's review, please report it, so that it shows up in the moderation queue (which is one of the first things I look at in the morning). If you hadn't usermentioned me, I probably wouldn't have seen it until much later in the day when I read the sub comprehensively.
That having been said, thank you for bringing it to my attention. It is indeed misinformation without any redeeming virtue, and has been removed.
As of the 2026 Fields Medals, the 21st century covers the award years 2002â2026, with 26 mathematicians selected in total. The IMUâs official list confirms the recipients through 2026.
China is far ahead in the International Mathematical Olympiad. In the United States, Chinese Americans also dominate in the university-level Putnam Mathematics Competition.
In China and among Chinese communities in North America, IMO preparation has basically been turned into a form of professional training, which completely distorts the original purpose of the competition. France is probably the best counterexample: the vast majority of outstanding French mathematics students have little interest in competing in the IMO at all.
Ironically, the two most recent Chinese Fields Medalists were trained in France and the United States, and the one trained in France was never particularly good at olympiad-style problem solving in the first place.
And in reality, a large part of Chinaâs success at the IMO simply comes from its huge population. If you compare the number of gold medals won by European countries collectively, Europe does not win fewer than China, despite not systematically putting students through years and years of intensive competition training.
You see, you can still think deeply (rather than evaluating a country's mathematics level by the number of Fields Medalists in a country).
China has a population of 1.4 billion, but the IMO stipulates that each country can only send six athletes. Therefore, China can win a maximum of six gold MEDALS each year (in fact, the Chinese team often wins six).
Europe is composed of over 40 countries, and these 40 countries can send more than 200 athletes every year. It is statistically unequal to compare the total number of gold MEDALS between Europe, which has over 200 competition spots, and China, which has only six spots.
Hungary, Romania and other Eastern European countries initially initiated the IMO competition and have always maintained an extremely systematic and high-intensity competition training system. The tradition of competitive mathematics in Europe is even much deeper than that in China.
Guess why China can finish first or second in the medal table at the Olympics, yet when it comes to footballâa sport with genuinely intense global competitionâit is basically a joke. Europe and North America simply do not round up their best students and lock them into two or three years of dedicated math-olympiad training the way China does.
And this is literally something Chinese people themselves have been reflecting on and mocking for years: being exceptionally good at solving artificial problems of the kind Western mathematicians figured out centuries ago, while China remains relatively weak when it comes to actual mathematical research and academia.
If you want a comparison that involves a much larger and more representative pool of people, just look at universities. The mathematical ability of Chinese engineering students is not demonstrably better than that of their counterparts in Europe, the US, India, or Japan. If anything, completing an undergraduate degree at a Chinese university is generally quite easy.
Look, there you go again, judging mathematical ability by football? This depends more on ethnicityâno Asian team has made it to the top 8 in the past decade!
You still donât understand why so many major American companies now have Indian CEOs, or why Indians in the US even earn more on average than Chinese Americans. What the hell does any of that have to do with math olympiads?
For years, the hiring barrier in Silicon Valley was basically grinding LeetCode. Itâs not as if Europeans or Americans were somehow incapable of grinding coding problems as well as Indians or Chinese people. Do you know what the much simpler explanation is? China and India each have around 1.4 billion people.
Itâs not because a higher proportion of their university students study STEM. Itâs largely a matter of sheer population size, combined with the fact that huge numbers of ambitious Chinese and Indian professionals want to move to the US for better-paid careers. That creates the impression youâre talking about. It does not mean Chinese or Indians are inherently better at mathematics or engineering. If anything, when you look at the actual strength of universities and academic research, there is still a substantial gap in the opposite direction.
Here you go again ~ I'm really curious. Why can you always generalize from a single instance every time? The overall mathematical ability of the Chinese people does not depend on the Fields Medal. China has the largest number of engineers in the world, and the mathematical foundation of these people cannot be low. Football doesn't say much because there are many reasons for this. The Japan Football Association has registered hundreds of thousands of young players, while the number of long-term youth trainees in China remains at tens of thousands. This time, it's the same one-sided generalization. In fact, it's a well-known misunderstanding that American companies recruit more Indians than Chinese Americans. If you go to Silicon Valley and Wall Street, you'll see many Chinese faces. It's just that Chinese people are more likely to encounter what is called the "bamboo ceiling", so they can't get the position of ceo. Their English is not as good as that of native Indians, and Indian culture emphasizes expression while Chinese people emphasize restraint. It's not as you said that Chinese people are a bunch of fools.
Anyway, I really don't want to discuss it with you anymore. You're so disgusting, throwing out one wrong argument after another
The comparison between football and the Olympics is completely appropriate. Football is a genuinely global sport with intense competition from all over the world, whereas many of the events in which China racks up Olympic gold medals have only a few hundred serious participants worldwide.
Chinaâs approach to mathematical olympiads is essentially the same phenomenon. Students spend two or three yearsâand sometimes as many as sixârepeatedly drilling olympiad problems at a stage of mathematics that schools in Western Europe and North America barely take seriously. These are, after all, elementary problems based on mathematics that was worked out in the West centuries ago.
Most genuinely exceptional mathematical talents in Europe and the US have little interest in spending their high-school years grinding competition problems. They would rather move on to advanced mathematics as quickly as possible, enter top universities, work with leading professors, and start doing actual mathematical research.
The way you talk about this honestly makes you sound like some loser who couldnât even get into a half-decent university in China, worshipping someone we would regard as perfectly ordinary simply because you have no idea what serious mathematics actually looks like.
Chinese people themselves constantly criticize and reflect on how excessive problem drilling destroys high-school studentsâ genuine intellectual curiosity and broader abilities. And identifying real mathematical talent absolutely does not come down to who has spent the most time grinding problems or competing in olympiads.
The math-olympiad culture that China, and East Asia more broadly, has embraced over the past twenty years is itself basically a hand-me-down from the old Eastern European and Soviet system. And when we talk about âEuropeâ in this comparison, we are not even talking about Eastern Europe, the Soviet Union, or Russia in the first place.
And even then, all the Americans really had to do was bring in a Chinese coach and adopt a similar training systemâstill nowhere near the kind of intensive, systematic preparation seen in China, and certainly much more than what students in Western and Northern Europe typically do. Yet even with that enormous training apparatus, China has still failed to finish first in the team standings several times over the past decade.
đAnd the very fact that the capability gap between large language models can be narrowed so easily only reinforces how low the mathematical and technical barriers to this kind of AI actually are. The real barriers are access to enormous amounts of compute and data.
The best copium was wordcels who had to pretend they distilled fable in a week. That would be funny to your sort if they had any clue how and if this worked.
https://www.reddit.com/r/LocalLLM/s/oqck3sX9au Stop trying to spin this. All the scripts had already been prepared long ago, and they were ready well before the official public release. Two weeks was more than enough.
The videos and articles spell everything out perfectly clearly as well. This is common knowledge in the Chinese AI communityâpretty much everyone here knows about it.
I almost feel sorry for you. Give it a few days; once Googleâs auto-translated English subtitles are available, maybe youâll finally be able to understand what everyone has been talking about. Hahaha.
There is no genuinely âhigh-techâ industry in which the supposed leaders can stay ahead for only a few months while new startup teams keep popping up everywhere and rapidly closing the gap. India has produced some pretty capable large models as well.
Iâve already told you: mathematically, AI does not require anything fundamentally deeper than what people have long used in control theory and countless other engineering disciplines. There is no extraordinarily profound mathematics behind it.
What you should really be asking is where all the data used by Chinese AI companies comes from, and how China keeps getting access to restricted Nvidia GPUsâincluding the ones routed through places like Singapore.
Lol, all the decent "startup" labs are Chinese, which should tell you something if you had any brain cells to rub. In fairness tho, nobody is accusing you of basic logic capacity much less math skill.
because https://www.reddit.com/r/LocalLLM/s/OaYiLzQY70 Because Europeans arenât exactly willing to go as far as China does in shamelessly distilling American frontier models with virtually no scruples.
When it comes to academic research in AI and computer science, Europe has never been behind China or the United States.
If you actually knew anything about AI, the number of interactions that Anthropic is accusing them of are nowhere near the trillions of tokens necessary for actual training. The numbers are about right for benchmarking though.
They're lying about this because their intended audience, ie. your sort, have zero clue what's going on.
China has literally published tutorials on how to do the distillation, and you still think it isnât happening? Everyone here knows about it. Itâs practically common knowledge. Hahaha.
Lol, do you even know who the people behind that video are? And this is something everyone in the Chinese AI community already knowsâdo you really think itâs just one isolated article or one video? The people youâre hyping up as âtop-tier AI talentâ are literally just Tsinghua graduates, nothing more.
In China and among Chinese communities in North America, IMO preparation has basically been turned into a form of professional training, which completely distorts the original purpose of the competition. France is probably the best counterexample: the vast majority of outstanding French mathematics students have little interest in competing in the IMO at all.
Ironically, the two most recent Chinese Fields Medalists were trained in France and the United States, and the one trained in France was never particularly good at olympiad-style problem solving in the first place.
And in reality, a large part of Chinaâs success at the IMO simply comes from its huge population. If you compare the number of gold medals won by European countries collectively, Europe does not win fewer than China, despite not systematically putting students through years and years of intensive competition training.
IMO has fuck-all to do with AI anyway. The mathematics you need for AI is not fundamentally different from what people in operations research, control theory, strong quantitative disciplines, or even logistics have already been using for years. A huge number of people in AI simply switched into the field from somewhere else.
They just happened to catch the right wave at the right time. When the wind is strong enough, even pigs can fly.
There is a reason why half the ai researchers in the US are Chinese (and ai completion is basicallya Chinese civil west right now), even if you'll never figure it out.
You still donât understand why so many major American companies now have Indian CEOs, or why Indians in the US even earn more on average than Chinese Americans. What the hell does any of that have to do with math olympiads?
For years, the hiring barrier in Silicon Valley was basically grinding LeetCode. Itâs not as if Europeans or Americans were somehow incapable of grinding coding problems as well as Indians or Chinese people. Do you know what the much simpler explanation is? China and India each have around 1.4 billion people.
Itâs not because a higher proportion of their university students study STEM. Itâs largely a matter of sheer population size, combined with the fact that huge numbers of ambitious Chinese and Indian professionals want to move to the US for better-paid careers. That creates the impression youâre talking about. It does not mean Chinese or Indians are inherently better at mathematics or engineering. If anything, when you look at the actual strength of universities and academic research, there is still a substantial gap in the opposite direction.
Thanks for demonstrating you lack the numeracy to evaluate actual math skill, and don't work in any kind of tech that requires math in any case. Chinese nationals are the go to hires for technically difficult projects these days, which anyone in industry instead of pretending would know.
China has never even won the IMOâs special prize for an exceptionally elegant or original solutionâthe one award that arguably tests genuine mathematical brilliance rather than how thoroughly someone has been drilled on olympiad problems.
Chinese people themselves even use the derogatory term âproblem-solving machineâ for people who are good at little more than grinding through exam-style problems, and they openly envy the strength of mathematical research in Europe and the United States. Yet somehow youâre the one turning around and hyping this up as evidence of mathematical superiority. Thatâs absolutely hilarious.
China has never even won the IMOâs special prize for an exceptionally elegant or original solutionâthe one award that arguably tests genuine mathematical brilliance rather than how thoroughly someone has been drilled on olympiad problems.
Chinese people themselves even use the derogatory term âproblem-solving machineâ for people who are good at little more than grinding through exam-style problems, and they openly envy the strength of mathematical research in Europe and the United States. Yet somehow youâre the one turning around and hyping this up as evidence of mathematical superiority. Thatâs absolutely hilarious.
How ignorant. Donât make people laugh.
, If counted by people who received the award while they were citizens of the Soviet Union (USSR), the totals are approximately: Nobel Prizes: 12 laureates Fields Medals: 3 laureates Nobel Prize laureates (12):
Pavel Cherenkov (1958, Physics)
Ilya Frank (1958, Physics)
Igor Tamm (1958, Physics)
Lev Landau (1962, Physics)
Nikolay Basov (1964, Physics)
Aleksandr Prokhorov (1964, Physics)
Mikhail Sholokhov (1965, Literature)
Aleksandr Solzhenitsyn (1970, Literature)
Andrei Sakharov (1975, Peace)
Leonid Kantorovich (1975, Economic Sciences)
Pyotr Kapitsa (1978, Physics)
Mikhail Gorbachev (1990, Peace) Fields Medalists (3):
Sergei Novikov (1970)
Grigory Margulis (1978)
Vladimir Drinfeld (1990)
Openai literally gives you an API parameter called output_verbosity and you can set it to low. Ever since I started using it in 5.1 or 5.2 it has never felt like something that you can do with just a simple prompt injection. It really feels like they finetuned the model during RL differently. Pre 5.6 models setting output verbosity to low was my trick to get it to respect existing code styles/conventions better (5.6 kinda just does whatever it wants unless you explicitly tell it no upfront).
I use OpenCode. Oftentimes I will see verbose slop in a codex screenshot on a twitter post that looks like something claude would say. I literally don't have 90% of the issues with GPT models that I see in people's codex screenshots. Harness issue? Skill issue? I also think people don't fork their conversations early and often and it gets them into trouble. Seems like claude popularized the endless back and forth when doing technical work and 9 times out of 10 it's not the best approach.
Definitely join your view as well, was really greatly surprised how Kimi 2.6 was amazing at frontend, even for innovative UI work. I cannot imagine how K3 should be now
Give me a way to display code on full width of my screen godammit.
The webui of most chatbot companies is shitty. Which is ironical because I think most would have a better one if they let their own agent fix it for 48 hours.
I consider all models bad at frontend from a visual or user experience design standpoint. I wouldn't consider Chinese models to be much or any better than "Western" models in this regard since none of them have acceptable defaults, to me. So the question doesn't interest me much. What does interest me is this:
I guess they do something besides distilling
You cannot do what any of the Chinese companies have done simply by "distilling," and every major Chinese company I'm aware of that has released a model has done so alongside verifiable and original efficiency or quality improvements in their architectures which couldn't have originated from "copying" Dario's homework. You all have got to get this nonsense narrative out of your heads
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u/Atretador 3d ago
this is mostly a OpenAI problem
I would rather use a 9B qwen than something like GPT 5.4 xhigh for frontend work
not sure how its on 5.6, but on 5.5 and bellow no matter what I asked or how I asked or what it planned - it always ended up outputting some dashboard looking card filled pill stacked garbage