Biggest pain point is still inference providers. Even decent labs like Ai2 or THUDM need to lobby for that. My leaderboard is for web developers but I can only evaluate the most visible models with token API support. https://huggingface.co/spaces/onekq-ai/WebApp1K-models-leaderboard
Maybe some players have GPUs but keep the results to themselves. We can only hope they will reciprocate for what they benefit from this community.
yes yes.
Maybe you can run a leaderboard of models indexed by freedom 🤗
I doubted there will be a Qwen3-coder. The direction changed. Alibaba is a corporation. You can imagine the number of executive sponsors for this release. Stock performance is at stake now. Price of success.
You meant the non-thinking mode? If so, add /no_think in your prompt
Noted. It thinks too long which is the problem. R1 and QwQ also took longer but are acceptable.
When I tested Qwen3, the difference of two modes is between an hour and a day (maybe longer)
+1
Ah thanks! this works
nice. what model is behind it.
That's a great start. Also see my post https://huggingface.co/posts/onekq/992154552707771
The point is models are already embedded and inferenced everywhere. If you standardize energy consumption as a inference output field, your impact is multiplied instantly because the groundwork is already there.
In theory, this works for closed-source model too.
Also would be great to have this in API response, then you have energy-aware leaderboards, workflows, etc.
