alt Hacker NewsYou have to read about half of the article before it mentions this, which should have been in the first paragraph:
> The researchers found the energy and accuracy disparity by measuring the amount of energy used by three open-source AI models, Alibaba’s Qwen 3, Google’s Gemma 3, and Meta’s Llama 3.1.
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Is the publishing cycle this long? Those models were relevant 18 months ago
Working out the kinks in your methodology obviously takes some time. But is there any structural reason not to rerun the benchmarks on current models in the final stages before submission? Assuming the results generalize to those newer models
How would one evaluate the energy consumption of models accessible only through Anthropic or OAI APIs? You can't fire them up on your own computers and measure power consumption.
I feel like that info is placed appropriately. The abstract mentions that energy disparity persists across models, the rest follows the standard Intro -> Related Work -> Experiments structure
Edit: sorry, i went straight to the paper. I agree, the article itself (and the headline) are bad (as they tend to be on this topic)