yeah it's kind of the point. they're pedagogical tools. they give you the full recipe for building it from scratch or fine-tuning it beyond what it is.

but i'm prepared to be surprised, maybe they'll conjure up something standalone useful this time

They have an incentive to produce a more finished model to go with the launch of the RTX Spark laptops, I guess.

Not really - you pay for the hardware. Everyone else already is building models for Spark hardware.

I think their entire pitch about local AI is best demonstrated with their own model that they can optimise for it, and the shape of this model seems optimised for the smaller RTX chips. Indeed, this model appears to be part of their launch picture:

https://blogs.nvidia.com/blog/local-ai-rtx-spark-laptops-sof...

Well, weights released:

https://huggingface.co/nvidia/NVIDIA-Nemotron-3.5-Super-VL-1...

And their own benchmarks seem to show it well behind of Qwen 3.8 flash next on pretty much everything except generation speed.

That's not the model onlyrealcuzzo is talking about. He is talking about the A9B that was just released five or six minutes ago.

Which is not going to compare well to the 3.8 Flash because it's much smaller; designed to fit quite a large model into quite a small space.

Will be interesting to see how it compares to Muse Glimmer, Qwen 3.8 27B and the older Qwen 3.6 35B (and how its image analysis performance compares to Gemma 4 12B QAT, which is still IMO the most interesting open weights model released all year).