Going to have to disagree on the backup test. Opus flamingo is actually on the pedals and seat with functional spokes and beak. In terms of adherence to physical reality Qwen is completely off. To me it's a little puzzling that someone would prefer the Qwen output.
I'd say the example actually does (vaguely) suggest that Qwen might be overfitting to the Pelican.
wongarsu 21 hours ago [-]
Qwen's flamingo is artistically far more interesting. It's a one-eyed flamingo with sunglasses and a bow tie who smokes pot. Meanwhile Opus just made a boring, somewhat dorky flamingo. Even the ground and sky are more interesting in Qwen's version
But in terms of making something physically plausible, Opus certainly got a lot closer
kmacdough 21 hours ago [-]
Given adherence is a more significant practical barrier, it's probably the better signal. That is, if we decide too look for signal here.
BobbyJo 17 hours ago [-]
The fundamental challenge of AI is preventing unprompted creativity. I can spin up a random initialization and call all of it's output avante garde if we want to get creative.
userbinator 17 hours ago [-]
I recently fell down the rabbithole of AI-generated videos, and realised that many of the "flaws" that make them distinctive, such as objects morphing and doing unusual things, would've been nearly impossible or require very advanced CGI to create.
doobiedowner 19 hours ago [-]
[flagged]
itake 14 hours ago [-]
"artistically interesting" is IMHO both a subjective and 'solved' problem. These models are trained with an "artistically interesting" reward model that tries to guide the model towards higher quality photos.
I think getting the models to generate realistic and proportional objects is a much harder and important challenge (remember when the models would generate 6 fingers?).
tpm 11 hours ago [-]
The Opus bike isn't very physically plausible though.
kube-system 16 hours ago [-]
Qwen, at least, can draw a complete bicycle frame. The opus frame will snap in half and can’t steer.
tecoholic 20 hours ago [-]
Even the first one - Qwen added extra details in the background sure. But he Pelican itself is a stork with a bent beak and it's feet is cut off it's legs. While impressive for a local model, I don't think it's a winner.
mejutoco 20 hours ago [-]
Did you see opus bike though for that same test? I know it is about the flamingo but that is bad.
irthomasthomas 19 hours ago [-]
It's a 3B model. It should not be this close. Debating their artistic qualities is missing the point.
monocasa 17 hours ago [-]
35B, but your point stands I think.
jbellis 22 hours ago [-]
For coding, qwen 3.6 35b a3b solved 11/98 of the Power Ranking tasks (best-of-two), compared to 10/98 for the same size qwen 3.5. So it's at best very slightly improved and not at all in the class of qwen 3.5 27b dense (26 solved) let alone opus (95/98 solved, for 4.6).
kristianp 20 hours ago [-]
This has similar problems to swe bench in that models are likely trained on the same open source projects that the benchmark uses.
If all models are trained on the benchmark data, you cannot extrapolate the benchmark scores to performance on unseen data, but the ranking of different models still tells you something. A model that solves 95/98 benchmark problems may turn out much worse than that in real life, but probably not much worse than the one that only solved 11/98 despite training on the benchmark problems.
This doesn't hold if some models trained on the benchmark and some didn't, but you can fix this by deliberately fine-tuning all models for the benchmark before comparing them. For more in-depth discussion of this, see https://mlbenchmarks.org/11-evaluating-language-models.html#...
__natty__ 21 hours ago [-]
You compare tiny modal for local inference vs propertiary, expensive frontier model. It would be more fair to compare against similar priced model or tiny frontier models like haiku, flash or gpt nano.
javawizard 21 hours ago [-]
Not when the article they're commenting on was doing literally exactly the same thing.
ericd 21 hours ago [-]
Eh it’s important perspective, lest someone start thinking they can drop $5k on a laptop and be free of Anthropic/OpenAI. Expensive lesson.
spwa4 8 hours ago [-]
It is much faster though. On my m1 max, describing a picture (quick way to get a pretty large context):
Qwen 3.6 35b a3b: 34 tok/sec
Qwen 3.5 27b: 10 tok/sec
Qwen 3.5 35b a3b: doesn't support image input
upboundspiral 6 minutes ago [-]
I've been using Qwen 3.5 35B-A3B with images as input so I suspect you perhaps didn't include the vision part of the model during testing (I use llama.cpp and I learned I needed to include the separate mmproj part).
21 hours ago [-]
mentalgear 22 hours ago [-]
I understand the 'fun factor' but at this point I really wonder what this pelican still proofs ? I mean, providers certainly could have adapted for it if they wanted, and if you want to test how well a model adapts to potential out of distribution contexts, it might be more worthwhile to mix different animals with different activity types (a whale on a skateboard) than always the same.
simonw 22 hours ago [-]
That's why I did the flamingo on a unicycle.
For a delightful moment this morning I thought I might have finally caught a model provider cheating by training for the pelican, but the flamingo convinced me that wasn't the case.
furyofantares 21 hours ago [-]
It is completely wild to me that you prefer Qwen's flamingo. I think it's really bad and Opus' is pretty good.
simonw 21 hours ago [-]
The Opus one doesn't even have a bowtie.
furyofantares 21 hours ago [-]
The Opus one looks like a flamingo, and looks like it's riding the unicycle. Sitting on the seat. Feet on the pedals.
The Qwen one looks like a 3-tailed, broken-winged, beakless (I guess? Is that offset white thing a beak? Or is it chewing on a pelican feather like it's a piece of straw?) monstrosity not sitting on the seat, with its one foot off the pedal (the other chopped off at the knee) of a malmanufactured wheel that has bonus spokes that are longer than the wheel.
But yeah, it does have a bowtie and sunglasses that you didn't ask for! Plus it says "<3 Flamingo on a Unicycle <3", which perhaps resolves all ambiguity.
bigyabai 19 hours ago [-]
Let's not oversell Opus' output. The Qwen flamingo is flawed but could be easily fixed with 1-2 prompts if you're really upset with it. The Opus SVG is not any better than something that I could make in Inkscape with 3 minutes and sufficient motivation. Calling Opus' flamingo "programmer art" would be an insult to programmers.
monksy 20 hours ago [-]
Game over opus
akavel 21 hours ago [-]
r/LocalLlama is now doing a horse in a racing car:
If I (commercially) made models I’d put specific care into producing SVGs of various animals doing (riding) various things ... I find it interesting how confident you seem to be that they’re not.
To me the opus flamingo is waaaay better than the qwen one. qwen has the better pelican, though.
dude250711 21 hours ago [-]
Is a flamingo on a unicycle not merely a special case of a pelican on a bicycle?
gistscience 10 hours ago [-]
Yeah I can imagine these popular benchmarks get special treatment in the training of new models. I wonder how they would perform for "Elephant riding a car" or "Lion sleeping in a bed"
luyu_wu 18 hours ago [-]
Consider reading the article, which addresses all of the points you raise.
It's directly stated in the post that the entire test is meant to be humorous, not taken seriously, only that is has vaguely followed model performance to date. The author also writes that this new result shows that trend has broken..
stephbook 20 hours ago [-]
They're certainly aware of the test, but a turtle doing a kickflip on a skateboard? I seriously doubt they train their models for that.
This is a gag that's long outlived its humor, but we're in a space so driven by hype there are people who will unironically take some signal from it. They'll swear up and down they know it's for fun, but let a great pelican come out and see if they don't wave it as proof the model is great alongside their carwash test.
wood_spirit 20 hours ago [-]
Such a disconnect from the minutes I’ve lost and given up on Gemini trying to get it to update a diagram in a slide today. The one shot joke stuff is great but trying to say “that is close but just make this small change” seems impossible. It’s the gap between toy and tool.
big-chungus4 10 hours ago [-]
I swear every single time someone says "my laptop" on hacker news, it's some insane MacBook that is more powerful than 98% computers out there
ralph84 15 hours ago [-]
You can just straight up ask Opus if it's good at generating images and it will say no. It has never been marketed as being for image generation.
henry2023 15 hours ago [-]
More and more I suspect OpenAI is generating comments on HN to try shift the discussion.
I’m not sure you’re a bot but this is the stereotypical comment being overly critical of anything where OpenAI is not superior or being overly supportive (see comments on the Codex post today) while clearly not understanding the discussed topic at all.
SJMG 14 hours ago [-]
His account is from 2016.
This is not refutation of astroturfing on HN, but in this case, I doubt it.
simonw 15 hours ago [-]
Claude is actually very good at SVGs, and it's genuinely useful. I have Claude knock out little SVG icons all the time.
Illustrations with SVGs of pelicans riding bicycles will never be useful, because pelicans can't ride bicycles.
th0ma5 10 hours ago [-]
[dead]
15 hours ago [-]
sailingcode 21 hours ago [-]
I'm an iguana and need to wash my bicycle in the carwash. Shall I walk or take the bus?
layer8 20 hours ago [-]
You should have the pelican ride it to the carwash and wash it for you.
DANmode 20 hours ago [-]
That’s a long walk! You should reserve a ride with $PartnerRideshareCo.
ucyo 10 hours ago [-]
[dead]
VHRanger 21 hours ago [-]
That's not surprising; Opus & Sonnet have been regressing on many non-coding tasks since about the 4.1 release in our testing
ineedasername 17 hours ago [-]
On thinking about the reasons this may be something at least slightly more than training on the task is the richness with which language is filled with spatial metaphors even in basic language not by laymen considered metaphor outside the field of linguistics proper, in which concepts eg Lakoff's analysis in "Metaphors we Live By and others are simply part of the field, (though unsurprisingly, among the HN crowd I've occasionally seen it brought up)
The amount of money you have in the bank may often "increase" or "decrease" but it also goes up and down, spatial. Concepts can be adjacent to each, orthogonal. Plenty more.
So, as models utilize weight more densely with more complex strategies learned during training the patterns & structure of these metaphors might also be deepened. Hmmm... another thing to add to the heap of future project-- trace down the geometry of activations in older/newer models of similar size with the same prompts containing such metaphors, or these pelican prompts, test the idea so it isn't just arm chair speculation.
f33d5173 19 hours ago [-]
I don't know what such a demo would prove in the first place. LLMs are good at things that they have been trained on, or are analogues of things they have been trained on. SVG generation isn't really an analogue to any task that we usually call on LLMs to do. Early models were bad at it because their training only had poor examples of it. At a certain point model companies decided it would be good PR to be halfway decent at generating SVGs, added a bunch of examples to the finetuning, and voila. They still aren't good enough to be useful for anything, and such improvements don't lead them to be good at anything else - likely the opposite - but it makes for cute demos.
I guess initially it would have been a silly way to demonstrate the effect of model size. But the size of the largest models stopped increasing a while ago, recent improvements are driven principally by optimizing for specific tasks. If you had some secret task that you knew they weren't training for then you could use that as a benchmark for how much the models are improving versus overfitting for their training set, but this is not that.
God bless these open models. Claude can’t subsidize its users forever and no one can afford 1200$ a month for llm credits.
bdangubic 4 hours ago [-]
> no one can afford 1200$ a month for llm credits.
you'd be surprised....
999900000999 4 hours ago [-]
A Blackwell pro is only 10k.
Will Claude constantly be able to deliver more value than rolling your own ?
I think the future is a bunch of just good enough models, which is what most people need. Not top of the line models that require millions in hardware to run
bdangubic 3 hours ago [-]
not that I disagree with you in principle but I see this the same was a "cloud" - 10's of thousands of companies could save gazillion dollars by hosting their infrastructure and yet they continue to pay insane amounts of moneys to AWSs and Azures and whatnots. While some company's future may as well be running local models I would venture a guess that vast majority will just eat the costs and pass on as much of it as they can to their customers...
999900000999 22 minutes ago [-]
Hmm, can we agree open models place a sort of price ceiling on what most companies will pay.
Eventually another cloud provider can just spin up a few llms vs paying whatever Claude demands
Quarrelsome 17 hours ago [-]
Maybe the next time we suspect they're optimising for the test, switch the next test to drawing "the cure for cancer".
atonse 15 hours ago [-]
Wonder what would happen if we unleashed Karpathy’s autoresearch on the pelican bicycle test. And had it read back the image to judge it.
Oh maybe it might continue to iterate on the existing drawing?
quux 16 hours ago [-]
This is a useless benchmark now a days, every model provider trains their models on making good pelicans. Some have even trained every combination of animal/mode of transportation
henry2023 15 hours ago [-]
Every model provider except OpenAI?
aliljet 21 hours ago [-]
I'm really curious about what competes with Claude Code to drive a local LLM like Qwen 3.6?
chabes 19 hours ago [-]
OpenCode or Pi are popular agent harnesses. Lots of IDEs integrate LLMs now. I believe there’s also a Qwen Code that exists, but I have yet to try it.
smashed 21 hours ago [-]
OpenCode?
comandillos 22 hours ago [-]
I've been using Qwen3.5-35B-A3B for a bit via open code and oMLX on M5 Max with 128Gb of RAM and I have to say it's impressively good for a model of that size. I've seen a huge jump in the quality of the tool calls and how well it handles the agentic workflow.
iib 22 hours ago [-]
This is about the newly release Qwen3.6. Just wanted to make sure you got that correctly.
maltyxxx 4 hours ago [-]
[dead]
bottlepalm 20 hours ago [-]
I really wish they spent some time training for computer use. This model is incapable of finding anywhere near the correct x,y coordinate of a simple object in a picture.
hopinhopout 10 hours ago [-]
LLM's really causing serious brainrot if html pelican drawings are a usage basis for your programming projects, even all these shitty benchmarks don't say or mean anything if companies secretly tweak them on the go
wongarsu 10 hours ago [-]
Most of the 'coding benchmarks' are deeply flawed too. This one at least makes it explicit
And so far, the ability to make SVGs of $animal on $ vehicle seems to correlate surprisingly well with model 'intelligence'
Havoc 17 hours ago [-]
Between the legs and the beak I'd still rate the opus pelican higher
JaggerFoo 20 hours ago [-]
FYI, using a 128GB M5 MacBook Pro, sourced from another article by the author.
lofaszvanitt 21 hours ago [-]
That Qwen flamingo on the unicycle is actually quite good. A work of art.
justinbaker84 20 hours ago [-]
I love this benchmark!
kburman 18 hours ago [-]
looks like opus have been nerfed from day1
yieldcrv 19 hours ago [-]
All those models that were just at version 1.x in 2024
That’s so wild
refulgentis 20 hours ago [-]
I liked both of Opus' better, it was very illuminating, in both cases I didn't see the error's Simon saw and wondered why Simon skipped over the errors I saw.
Pelican: saturated!
jedisct1 21 hours ago [-]
I'm currently testing Qwen3.6-35B-A3B with https://swival.dev for security reviews.
It's pretty good at finding bugs, but not so good at writing patches to fix them.
nba456_ 19 hours ago [-]
Good reminder that these tests have always been useless, even before they started training on it.
tmatsuzaki 16 hours ago [-]
[dead]
aimadetools 7 hours ago [-]
[dead]
whywhywhywhy 19 hours ago [-]
[flagged]
simonw 19 hours ago [-]
If they're testing against it why do most of their attempts suck so much?
simon_is_genius 20 hours ago [-]
[flagged]
19qUq 22 hours ago [-]
How about switching to MechaStalin on a tricycle? It gets kind of boring.
mvanbaak 21 hours ago [-]
boring ... the ways all the models fail at a simple task never gets boring to me
throwuxiytayq 21 hours ago [-]
I literally cannot believe that people are wasting their time doing this either as a benchmark or for fun. After every single language model release, no less.
sharkjacobs 21 hours ago [-]
It feels like the results stopped being interesting a little while ago but the practice has become part of simonw's brand, and it gives him something to post even when there is nothing interesting to say about another incremental improvement to a model, and so I don't imagine he'll stop.
stephbook 20 hours ago [-]
I, for one, expected progress. Uneven, sometimes delayed, but ever increasing progress.
But that Opus pelican?
cedws 19 hours ago [-]
It’s not a waste of time.
As the boundaries of AI are pushed we increasingly struggle to define what intelligence actually is. It becomes more useful to test what models cannot do instead of what they can. Random tasks like the pelican test can show how general the intelligence really is, putting aside the obvious flaw that the labs can optimise for such a simple public benchmark.
throwuxiytayq 10 hours ago [-]
The whole point of this benchmark is that it asks the model to work in a modality it is not trained in and does not understand well. The result is largely meaningless. This is just like the people who are endlessly surprised by the fact that a raw LLM does not work with numbers well, or miscounts letters. In short, this test benchmarks the intelligence of the person running it, not of the model.
recursive 19 hours ago [-]
Fun is so un-productive. Everyone doing things for "fun" is going to be sorry when they look back and realizes they were wasting time having a "good time" rather than optimizing their KPIs.
throwuxiytayq 10 hours ago [-]
Sarcasm aside, asking LLMs do draw pelicans is your idea of fun? I'm worried for you.
bschwindHN 15 hours ago [-]
I do wonder how much energy collectively has been burned on this useless "benchmark".
segmondy 20 hours ago [-]
I can't believe you're such a party pooper. It's exciting times, the silly things do matter!
Marciplan 18 hours ago [-]
I also can't understand how this goes so viral every time on Hackernews lol
I'd say the example actually does (vaguely) suggest that Qwen might be overfitting to the Pelican.
But in terms of making something physically plausible, Opus certainly got a lot closer
I think getting the models to generate realistic and proportional objects is a much harder and important challenge (remember when the models would generate 6 fingers?).
https://blog.brokk.ai/introducing-the-brokk-power-ranking/
This doesn't hold if some models trained on the benchmark and some didn't, but you can fix this by deliberately fine-tuning all models for the benchmark before comparing them. For more in-depth discussion of this, see https://mlbenchmarks.org/11-evaluating-language-models.html#...
Qwen 3.6 35b a3b: 34 tok/sec
Qwen 3.5 27b: 10 tok/sec
Qwen 3.5 35b a3b: doesn't support image input
For a delightful moment this morning I thought I might have finally caught a model provider cheating by training for the pelican, but the flamingo convinced me that wasn't the case.
The Qwen one looks like a 3-tailed, broken-winged, beakless (I guess? Is that offset white thing a beak? Or is it chewing on a pelican feather like it's a piece of straw?) monstrosity not sitting on the seat, with its one foot off the pedal (the other chopped off at the knee) of a malmanufactured wheel that has bonus spokes that are longer than the wheel.
But yeah, it does have a bowtie and sunglasses that you didn't ask for! Plus it says "<3 Flamingo on a Unicycle <3", which perhaps resolves all ambiguity.
https://redd.it/1slz38i
It's directly stated in the post that the entire test is meant to be humorous, not taken seriously, only that is has vaguely followed model performance to date. The author also writes that this new result shows that trend has broken..
https://x.com/JeffDean/status/2024525132266688757
If anything, the disastrous Opus4.7 pelican shows us they don't pelicanmaxx
I’m not sure you’re a bot but this is the stereotypical comment being overly critical of anything where OpenAI is not superior or being overly supportive (see comments on the Codex post today) while clearly not understanding the discussed topic at all.
This is not refutation of astroturfing on HN, but in this case, I doubt it.
Illustrations with SVGs of pelicans riding bicycles will never be useful, because pelicans can't ride bicycles.
The amount of money you have in the bank may often "increase" or "decrease" but it also goes up and down, spatial. Concepts can be adjacent to each, orthogonal. Plenty more.
So, as models utilize weight more densely with more complex strategies learned during training the patterns & structure of these metaphors might also be deepened. Hmmm... another thing to add to the heap of future project-- trace down the geometry of activations in older/newer models of similar size with the same prompts containing such metaphors, or these pelican prompts, test the idea so it isn't just arm chair speculation.
I guess initially it would have been a silly way to demonstrate the effect of model size. But the size of the largest models stopped increasing a while ago, recent improvements are driven principally by optimizing for specific tasks. If you had some secret task that you knew they weren't training for then you could use that as a benchmark for how much the models are improving versus overfitting for their training set, but this is not that.
God bless these open models. Claude can’t subsidize its users forever and no one can afford 1200$ a month for llm credits.
you'd be surprised....
Will Claude constantly be able to deliver more value than rolling your own ?
I think the future is a bunch of just good enough models, which is what most people need. Not top of the line models that require millions in hardware to run
Eventually another cloud provider can just spin up a few llms vs paying whatever Claude demands
Oh maybe it might continue to iterate on the existing drawing?
And so far, the ability to make SVGs of $animal on $ vehicle seems to correlate surprisingly well with model 'intelligence'
That’s so wild
Pelican: saturated!
It's pretty good at finding bugs, but not so good at writing patches to fix them.
But that Opus pelican?