I'd like to mention the Little Dorrit Benchmark [1] which I have been running for a couple of years now. It has a few nice features:
1. It tests visual reasoning and structured output in a single task.
2. It seems to sort correctly on advancing general intelligence. As a counterexample, if I'm not misremembering, artificialanalysis.ai made some changes to their benchmark recently after Astra ranked below several older models.
3. While models have gotten significantly better in the past 2 years, the top model is still at 0.78 F1, so the test is not yet saturated. As a reference point, when I started, the top models were in the [0.1, 0.2] range.
Website looks very cool, Fable's octopus-organist looks very cute, but I feel like this benchmark (generate an SVG by a short and slightly ridiculous description) in general has been completely Goodharted [0].
I think they all just added a bunch of similar tasks to their training sets, so we cannot judge true emergent capabilities of the models anymore.
I don't think a bunch of similar tasks can really saturate the "create a SVG of X", because the model should have a quite good spatial understanding of the world and how everything interacts.
For example Gemini 3.8 Flash seems very impressive at first glance but the results are not actually very coherent, this shows that its "world model" is not particularly great (compare to SOTA models).
All models are pretty good now at generating these images. Back in the day, I remember experimenting with the pelican images and most of the models couldn't align the legs with the wheels. Right now as well, GPT messed up an octopus leg by originating it through the instrument rather than the octopus itself.
I think that intertwining two entities (living/non-living) is still challenging but overall they're pretty sound.
I'd like to mention the Little Dorrit Benchmark [1] which I have been running for a couple of years now. It has a few nice features:
1. It tests visual reasoning and structured output in a single task.
2. It seems to sort correctly on advancing general intelligence. As a counterexample, if I'm not misremembering, artificialanalysis.ai made some changes to their benchmark recently after Astra ranked below several older models.
3. While models have gotten significantly better in the past 2 years, the top model is still at 0.78 F1, so the test is not yet saturated. As a reference point, when I started, the top models were in the [0.1, 0.2] range.
[1] https://dorrit.pairsys.ai/
Website looks very cool, Fable's octopus-organist looks very cute, but I feel like this benchmark (generate an SVG by a short and slightly ridiculous description) in general has been completely Goodharted [0].
I think they all just added a bunch of similar tasks to their training sets, so we cannot judge true emergent capabilities of the models anymore.
[0] https://en.wikipedia.org/wiki/Goodhart%27s_law
I don't think a bunch of similar tasks can really saturate the "create a SVG of X", because the model should have a quite good spatial understanding of the world and how everything interacts.
For example Gemini 3.8 Flash seems very impressive at first glance but the results are not actually very coherent, this shows that its "world model" is not particularly great (compare to SOTA models).
All models are pretty good now at generating these images. Back in the day, I remember experimenting with the pelican images and most of the models couldn't align the legs with the wheels. Right now as well, GPT messed up an octopus leg by originating it through the instrument rather than the octopus itself.
I think that intertwining two entities (living/non-living) is still challenging but overall they're pretty sound.
All models are pretty good now at generating these images.
Not zebras. If you want to see how bad SVG output still is, ask for a zebra riding a scooter.
Gemini 3.8 flash seems to (subjectively) be the outlier in terms of performance to cost ratio?
Gemini 3.8 Flash results are often not very coherent but it does put a lot of shading and details to hide the fact.
Well that benchmark is now saturated, what next. How fast you can hack the pentagon?
Does a test of instructions how to fold origami figures in a SVG/jpeg exist? Or could be useful?
Feels like google has a different training set than the others?
Interesting, out of all examples Gemini 3.8 is the best for me. Also the image style is different and more vibrant than others
> An elephant typing on a typewriter
A monkey, surely?
Asking to animate it add an interesting layer of difficulty