Number of params isn’t really the relevant metric imo. Top models don’t support local inference. More relevant is tokens per dollar or per second.
Number of params isn’t really the relevant metric imo. Top models don’t support local inference. More relevant is tokens per dollar or per second.
Its an open source model, why wouldn't it be relevant for people who want to self host.....
This one is open weights but comparing to Gemini/Claude etc. on number of params isn’t relevant outside of a research context imo. Users don’t care how many params Gemini has as long as it’s fast and cheap.
Number of parameters is at least a proxy for model capability.
You can achieve incredible tok/dollar or tok/sec with Qwen3 0.6b.
It just won't be very good for most use cases.
Model capability is the other axis on their chart. So they could have put Qwen 0.6b there, it would be in the bottom right corner.
I know what they are trying to do. They are attempting show a kind of pareto frontier but it’s a little awkward.
It does since you can run this model locally on a < $3k machine