No, it doesn't mean anything because it's not been uploaded yet. You won't have the hardware to run it in any meaningful way, pretty much nobody really has 😄
No, the weights are either still bring uploaded or built so the only thing in the repository is an mmproj vision module, thus tricking HF's parameter algorithm to think the model is 0.4b params. Once everything is uploaded it will show the correct parameter count of 2.8T.
You won't have the hardware to run it in any meaningful way, pretty much nobody really has 😄
In 1–2 years, things could look very different when it comes to hardware, and with the right quantization... ;) I think it's generally a good thing that very powerful models are being offered for free—it gives me some hope.
You won't have the hardware to run it in any meaningful way, pretty much nobody really has 😄
In 1–2 years, things could look very different when it comes to hardware, and with the right quantization... ;) I think it's generally a good thing that very powerful models are being offered for free—it gives me some hope.
However, in 1-2 years, new models will most likely far surpass this one at much lower sizes - just look at qwen3.6 27b which is smarter than GPT-5.
You won't have the hardware to run it in any meaningful way, pretty much nobody really has 😄
In 1–2 years, things could look very different when it comes to hardware, and with the right quantization... ;) I think it's generally a good thing that very powerful models are being offered for free—it gives me some hope.
However, in 1-2 years, new models will most likely far surpass this one at much lower sizes - just look at qwen3.6 27b which is smarter than GPT-5.
In theory, in certain benchmarks maybe or if you compare small-scope one-shot questions. However, in reality for meaningful agentic workflows with sufficiently complex problems size matters. And IMHO, small models like qwen27B already break down much earlier than that - even as BF16.
