Pelican for Fable 5 on default settings is a clear improvement on Opus 4.8
Fable 5 default: https://gist.github.com/simonw/036bee5a703e7ec84e34efa974438...
Opus 4.8 (the "max" one is closest to Fable): https://simonwillison.net/2026/May/28/claude-opus-4-8/#and-s...
Now here are the Fable pelicans for all five of the thinking effort levels - low, medium, high, xhigh, max: https://tools.simonwillison.net/markdown-svg-renderer#url=ht...
Low used 25 input, 1,929 output - 9.67 cents: https://www.llm-prices.com/#it=25&ot=1929&sel=claude-fable-5
Max used 25 input, 14,430 output - 72.175 cents! https://www.llm-prices.com/#it=25&ot=14430&sel=claude-fable-...
The pelican has looked very same-y across all frontier models, same color bike, same camera angle, etc. I suspect this challenge is already too embedded in the training data to be a good signal when it succeeds, and maybe even when it fails in pathological ways mirroring existing AI pelicans on the internet.
I'd say it's working great for its intended purpose. Keeps Simon on top of all these threads and funnels traffic to his site.
True that
Do you seriously have a dedicated “bad takes on AI” hn account?
yeah, although I do combine it with "replies to snarky questions" for efficiency
I really don't understand what's interesting about this test and why is it always on top.
It's funny.
It really is lol
As often happens with random oddball things which become traditions in web communities, the replies asking what it is or complaining about it, begin to gain their own humor value.
Same reason you would always see the same top comments on reddit during a certain era.
That’s what I think too, but we should actively go against such culture here because hn is not reddit.
It basically is at this point, if you haven’t noticed. Complete with the same America bad, Elon bad, democrats good midwit progressive politics.
Elon does suck. Objectively.
Don't forget EU bad! Because they won't let Apple screw over consumers.
Is this Straw Man and Ad Hominem ?
Almost all Musk related negative news gets [flagged] and never hits the the front page, so there is still a silent base on the other "team" apparently.
It's a meme, and HN loves upvoting memes. Just like Reddit!
because you can't still ask LLMs to port DOOM to hardware X or Y
It has become a funny meme, much like "My hovercraft is full of eels!"
The ultimate measure of an LLM is whether it can produce a capable image of a pelican riding a bicycle. All other use cases are but a distraction!
Variations of this comment have been posted for over a year. The pelican has now morphed into part of HN culture rather than a legitimate benchmark, but it's still valuable as a meme.
it is more an example of gaming (the HN system) than meme.
Was it ever a good test? How do you even objectively assess what a good pelican on a bike is anyway?
SVG generation is a good test because it's extremely easy to subjectively assess with visual reasoning where humans are strong. However, pelican on a bike specifically may be overused at this point.
Do you think the models are ready for the next level? I believe that would be: Pelican feeding Spaghetti to Will Smith.
I'd be very surprised if this is in the training data given that most models mess it up to this day. E.g. look at the ones from Opus.
The "big beak!" comment in the svg source makes me think it's definitely a gamed "benchmark" at this point.
I'm beginning to wonder how much of a useful metric the pelican is because surely the frontier labs must be training their models on pelican-artistry because of how well known your test is now?
I've seen this reply to Simon's benchmark for 2 years running now, and yet you still see improvements and objectively-bad results over time from new releases, even when I'm sure every frontier AI team has/had a person at least partially dedicated to better bicycle-pelican SVG outputs. Alas.
I had intended to caveat that: I'm sure I'm not the first person to ask about this!
> you still see improvements
This is expected if they are training their models on it, right?
> objectively-bad results
Keen to learn when this has been the case, i.e. across version increments in major models.
I've written about this a couple of times, most notably here: https://simonwillison.net/2025/Nov/13/training-for-pelicans-...
I've been enjoying seeing how the quality of individual models differ based on the amount of reasoning effort you give them. If they were baking an a good pelican you wouldn't expect them to differ so much.
(Google Gemini are the only lab that have very clearly paid attention to the quality of SVG animals-riding-vehicles, see their announcement for Gemini 3.1: https://twitter.com/JeffDean/status/2024525132266688757 )
Amazing, thank you Simon! Look forward to reading.
I honestly assumed their comment was tongue in cheek humour, because positively no one actually cares how these models generate an SVG pelican riding a bicycle. It's some meme thing that this stuff always appears here.
Yeah this is not a real benchmark, it's just a fun tradition everytime a new model is released
"fun" / boringly predictable meme thread with 30+ replies already
It is telling that people need to create throwaway accounts to criticize simonw's behavior in this website.
Hence it has become a meta-benchmark of relative progress in SVG image generation of a known target which has leaked into the training data and for which "every frontier AI team has/had a person at least partially dedicated to" at least checking if not optimizing.
I don't know. Just looking at the bike frames (specifically the fact that the AI generated bikes have rather unsteerable front forks), it's clear to me that frontier labs aren't spending much time tuning models to make bikes look coherent, which I assume is an easier task than making a pelican riding a bike look coherent.
I just run my own benchmark for "draw an SVG with $animal driving $vehicle". I won't post my choice of animal and mode of transport, but there are plenty of uncommon combinations to choose from. So far it's a fun and visually intuitive benchmark that does seem to correlate with model capabilities
Simon has addressed this on virtually every new model release. He also has unpublished alternate prompts. But the larger point is: this is a fun experiment, not a serious and objective benchmark.
It's silly and a joke and a surprisingly good benchmark and don't take it seriously but don't take not taking it seriously seriously and if it's too good we use another prompt but don't actually because then it's not the pelican post and there's obvious ways to better it and it's not worth doing because it's not serious.
Only coherent move at this point: hit the minus button immediately. There's never anything about the model in the thread other than simon's post.
But what if they are better at flamingos? Are they optimized for pelicans? How about “draw me a four headed owl”? The meme, I get it, but I’d settle for a working bash script, tbh.
It was a completely useless test even before the labs trained for it.
Yes, it's always been published as a joke. You've explained why it was (and still is) funny meta-commentary on AI benchmarks.
The way I see it the benefit of benchmark isn't to take Simon's results at face value. It's a template for your own benchmarks that are easy to visually evaluate.
It's evolved from a funny, unserious benchmark to a tradition. When a major new model is released, I now always check the HN thread for Simon's Pelican post. I'll be sad when I don't find it.
When it started, comparing the progress between models was mildly interesting but everyone (including Simon) acknowledges it certainly leaked into the training data long ago.
This is the reply I look for in all the new model announcements. Its fun to tell people that I judge models based on pelicans.
Now someone post the link about how it’s impossible for humans to draw a bike from memory.
https://link.springer.com/article/10.3758/BF03195929
This is all we need, that moment the Pelican put the leg behind the frame, we are all doomed.
I also look for this reply because i like seeing the follow-up reply saying that this is not a benchmark anymore because labs have gotten it in their training data.
that reply never failed to come it's basically a meme at this point
It also does A LOT better, for my hamster test: https://aibenchy.com/showcase/?q=claude#showcase=6efb87c28e3...
I find it quite interesting that while the picture looks better the more advanced the model is, but apparently none so far "understands" that the pelicans legs are on both sides of the bike / top bar.
If you scroll to the bottom of the Fable-5 by effort page, Max effort actually gets this correct! (Along with being the only one I've seen so far to make a bicycle frame that matches the shape of what most bikes on Google images look like)
And the only one linked here that includes a bicycle chain!
It's interesting that they still get the head tube / handle bar part wrong.
Or the hands not being wings
The Max version gets more details right. The bike frame looks good, the chain, the wings are appropriately styled instead of “arms”, and the knee is bent, etc. Obviously we’re hitting marginal returns now, but I see differences.
How much money do you think they spent fine-tuning on pelican SVG generation?
Probably none. They probably have much better targets to optimize for than an SVG pelican or even SVGs in general.
Not as much as Qwen, since apparently 3.6 35B surpassed Opus 4.7 https://x.com/simonw/status/2044830134885306701
It's interesting that Gemini 3(.1?) Deep Think is still the best at this task and it's still not really generally available. Maybe Fable could match it at higher effort levels? https://simonwillison.net/2026/Feb/12/gemini-3-deep-think/
Can you please compare the code generated by other similar quality pelicans by other models. Code in your first link (Fable 5 Default) looks minimal yet very good.
Looks like Fable constructed the "max" "looking" pelican of the previous model for the "xhigh" output token count of the previous model.
Is it possible to use the credits from subscription (https://support.claude.com/en/articles/15036540-use-the-clau...) for fable?
I'm pretty sure they're optimizing the models around these sorts of tests.
Anyone care about these pelicans that always come up anymore?
Clearly at this point they are part of the training data.
They even all look sort of ish the same. Daytime, colors,...
Without being mean, I encourage you to go look at some of simonw's writing on this topic, which he has addressed repeatedly (and IMO satisfactorily.)
I know because I too had this initial take; however, upon analysis, it is not sound.
I know he is an AI influencer that promotes his blog any chance he gets.
I agree as well that he writes many interesting things.
I could be tripping but I’m sure that is very similar to the Deepseek one from not long ago. Clearly I am too lazy to go and find it for verification.
Yay, max level actually put one of the legs behind the frame!
Personally feel like it could be more ambitious with what it creates.
Where is the clear improvement on Fable 5? The tail is misplaced.
Why always sunny days?
Pelicans hate biking in the rain (as do I).
Fable 5 xhigh actually looks the best to me.
Do we need a pelican every single time a model is released? Beating a very dead horse.
Fun at first, seems disingenuous now. A site funnel
The way they talked it up, having both legs on one side of the bike is like walking to the car wash
that's a great looking pelican
need more Alex Moulton style bikes
dude, the max version looks like it's finally there. handle bar holding with wings, the left leg is behind the frame while the right is in front of it (correctly).
well done anthropic.
mediocre pelican. very disappointing
How many barrels of oil are burned per pelican at Fable levels?