Phi-4-reasoning-vision and the lessons of training a multimodal reasoning model

Absolutely. I look forward to a time where we have on-device small models as an OS-level service you can rely on (a bit like what Apple's doing with Foundation Models). I was recently playing around with some game dev prototyping where I wish I could rely on a player having access to a local model for doing some classification tasks or generating small amounts of playthrough-specific copy without just populating the same few templates.

I get excited for every new vision model, especially those that work better and more efficiently. Vision is where we are so very far behind.. I can’t wrap my head around it

Small local models are the only thing that still have that magic feeling to me. While large models are still useful and impressive, it makes more sense that they are happening on a giant super computer in a datacenter somewhere. But all the intelligence and capability that can run on my mid level gaming PC is astonishing to me.

I absolutely love it.

Am so much more excited about tiny models gaining real intelligence. Just today I have been running Qwen3.5 0.8B model on images and am pleasantly surprised by how good it is compared to even 4B and 8B models from a few months ago.

I'm very happy to read about this progress but I don't find it particularly surprising. The big labs optimize for accuracy/high scores on benchmarks first; I automatically expect that (with some research effort) a model with 100x few parameters can achieve the same scores.

yes! especially b/c i want to process a lot of email and directories full of old, personal documents