I haven't evaluated this one, but for what I have, it seem the pplx-decider-v1.2 (and its -flash variant) are pretty good. Anyone evaluated all these open-source decision models on their own tasks? (I evaluated on MonitoringBench).
Have you checked mammoth-1/elephant-1 models? They are benchmarking quite well compared and are currently free on openrouter. I currently use mammoth-1 for a small internal app and it works flawlessly for what I am doing.
Ah damn and also interesting. I am using it for classifying ads in podcasts. I am listening to a lot of English podcasts, but I am in Germany so often German segments are cut in. Mammoth-1 has had zero issues classifying those segments, but I guess my usecase might just be a lot simpler than yours.
This is really AI slop - so I don’t really know if it makes any sense for comments given that there is no real way to validate the crap that was put out.
It seems somebody bought the domain due to its rating. All the authors share the same type of image for their profile pics…
It’s sad that this content now come to the top of HN so often
Put a decision model in my bike that decides when it is time to automatically shift up/down based on signals (FTP, Watt avg, HR, cadence, upcoming grade) and I will buy a subscription to your SaaS.
It's a meme. Simon Willison started doing it because, I'm paraphrasing, it's something that (at the time) was just sort of at the edge of what you could expect an LLM to be able to do, and also it's somewhat of an impossible task since, of course, Pellicans can't ride bicycles. From there, he started writing about it along with every major LLM release he covered. His coverage is generally well regarded (hi, Simon!) and so it sticks around. It's never been intended as a serious benchmark.
already , i self hosted Deekseek 4.1 Flash , Qwen 3.8 Flash Next , Glm 5.3 flash , tested it , all benchmaxxed to the point that all of them can draw that well , much better than other logos .
I recall that when this benchmark came out there were concerns that AI companies were gaming benchmarks to fake their progress. The purpose was to find something silly and outlandish that AI companies would definitely not have trained their models on, and thus have a way to check a model's capabilities.
A pelican riding a bicycle is pretty random. That was the whole point.
Could one reverse the test? Feed ai generated svgs into the model and ask it to decide which of 10 animals (dog, cat, pelican, crocodile, etc) doing which of 10 actions (moonwalking, paddleboarding, sitting, riding a bicycle, etc.).
Unlike the Internet, Microsoft did recognise the pivotal moment. But they made the wrong play… that and they’ve annoyed pretty much everybody with their products, I don’t think I’ve ever seen such a successful company with such little good will from their community.
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[ 10.6 ms ] story [ 481 ms ] threadThe only one that came close to Jev itself was the one from respan, which is also open source and cheaper too.
https://huggingface.co/baselabs/mammoth-1
You might also be interested in this index for decision models: https://huggingface.co/spaces/multimodalart/jev-decision-ind...
Thanks for the index. I will try to navigate it. For now I cannot even find this respan/span-02 in it :/
It seems somebody bought the domain due to its rating. All the authors share the same type of image for their profile pics…
It’s sad that this content now come to the top of HN so often
This made me realize it's been a long time since I did some brainstorming and how I missed it.
The pelican meme is so much better than benchmaxxed stuff. Unfortunately we are likely now in pelicanmaxxing territory.
I recall that when this benchmark came out there were concerns that AI companies were gaming benchmarks to fake their progress. The purpose was to find something silly and outlandish that AI companies would definitely not have trained their models on, and thus have a way to check a model's capabilities.
A pelican riding a bicycle is pretty random. That was the whole point.
Sorry i reply to wrong comment.
AI slop reporting. Actual news: https://commandline.microsoft.com/microsoft-decision-1-model...