I like the idea of more comparisons of models. Are there plans to add independent analyses of these models or is it only an aggregation of input limits?
How do you see this differing from or adding to other analyses such as:
Great! I wish there was a "bang to buck" value. Some way to know the cheapest model I could use for creating structured data from unstructured text, reliably. Using gpt4o-mini which is cheap but wouldn't know if anything cheaper could do the job too.
I'd like to share a personal perspective/rant on AI that might resonate with others: like many, I'm incredibly excited about this AI moment. The urge to dive headfirst into the field and contribute is natural after all, it's the frontier of innovation right now.
But I think this moment mirrors financial markets during times of frenzy. When markets are volatile, one common piece of advice is to “wait and see”. Similarly, in AI, so many brilliant minds and organizations are racing to create groundbreaking innovations. Often, what you're envisioning as your next big project might already be happening, or will soon be, somewhere else in the world.
Adopting a “wait and see” strategy could be surprisingly effective. Instead of rushing in, let the dust settle, observe trends, and focus on leveraging what emerges. In a way, the entire AI ecosystem is working for you: building the foundations for your next big idea.
That said, this doesn't mean you can't integrate the state of the art into your own (working) products and services.
Tangent question: is there anything better on the desktop than ChatGPT's native client? I find it too simple to organize chats but I'm having a hard time evaluating the dozen or so apps (most are disguise for some company's API service). Any recommendations? macOS/Linux compatibility preferred.
vunderba ·19 days ago
https://whatllm.vercel.app
The tables are very similar - though you've added a custom calculator which is a nice touch.
Also for the Versus Comparison, it might be nice to have a checkbox that when clicked highlights the superlative fields of each LLM at a glance.
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ursaguild ·19 days ago
How do you see this differing from or adding to other analyses such as:
https://artificialanalysis.ai
https://huggingface.co/spaces/TTS-AGI/TTS-Arena
https://huggingface.co/spaces/hf-audio/open_asr_leaderboard
https://huggingface.co/spaces/TIGER-Lab/GenAI-Arena
Great work on all the aggregation. The website is nice to navigate.
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karpatic ·19 days ago
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wslh ·19 days ago
But I think this moment mirrors financial markets during times of frenzy. When markets are volatile, one common piece of advice is to “wait and see”. Similarly, in AI, so many brilliant minds and organizations are racing to create groundbreaking innovations. Often, what you're envisioning as your next big project might already be happening, or will soon be, somewhere else in the world.
Adopting a “wait and see” strategy could be surprisingly effective. Instead of rushing in, let the dust settle, observe trends, and focus on leveraging what emerges. In a way, the entire AI ecosystem is working for you: building the foundations for your next big idea.
That said, this doesn't mean you can't integrate the state of the art into your own (working) products and services.
Show replies
gtirloni ·19 days ago
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