Also, open-weights models are more expensive per task than Haiku and Luna
Yes they are, but you should understand what is the defining feature of a local model. Being able to run them locally is a consequence of that defining feature, not the defining feature. And it turns out that it makes them cheaper to run.
Moreover, you can run both local models and non-local open weights models through providers such as OpenRouter. They evem have Qwen2.5 7B.
> Also, open-weights models are more expensive per task than Haiku and Luna
You should really check your notes. Luna only remained competitive because OpenAI was forced to halve its cost just to avoid being dominated by open weight models. I seriously recommend you check out OpenRouter's benchmarks.
I checked. OpenRouter provides their own. They use their actual cost, which is what they charge users, and their benchmarks results. Please, spend a few minutes to browse it. You'll notice that the likes of Luna is dominated by quite a few entries.
We should check it in few months after IPO
That's hardly relevant. I can use any local model through providers such as OpenRouter and get blazing fast prompt response times, and you're charged a small of what an OpenAI/Anthropic prompt costs.
What makes local models extremely competitive is the fact you do not need a huge data center to run them. The hardware they require is far from impressive. Check Mac studio benchmarks and how some models output >200token/second.