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Moondream 3 Preview: Frontier-level reasoning at a blazing speed

moondream.ai

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Re: Moondream 3 Preview: Frontier-level reasoning at a blazing speed

#5
post #3

I tried it out on their website and it seems pretty legit, it gets stuff wrong but so do all the vision models in my experience

Especially good at detection & pointing cases - especially since the bigger models aren't good at localization

Re: Moondream 3 Preview: Frontier-level reasoning at a blazing speed

#6
post #2

That’s actually kinda impressive for an 8b model. Normally my experience with them is that they’re not really useful.

Only 2b active also - very fast

Can run it on a phone then?

Seems like it could be somewhat useful for people with poor eyesight or blindness

Re: Moondream 3 Preview: Frontier-level reasoning at a blazing speed

#7
Moondream 2 has been very useful for me: I've been using it to automatically label object detection datasets for novel classes and distill an orders of magnitude smaller but similarly accurate CNN.

One oddity is that I haven't seen the claimed improvements beyond the 2025-01-09 tag - subsequent releases improve recall but degrade precision pretty significantly. It'd be amazing if object detection VLMs like this reported class confidences to better address this issue. That said, having a dedicated object detection API is very nice and absent from other models/wrappers AFAIK.

Looking forward to Moondream 3 post-inference optimizations. Congrats to the team. The founder Vik is a great follow on X if that's your thing.

Re: Moondream 3 Preview: Frontier-level reasoning at a blazing speed

#8

Earlier quoted context omitted.

Only 2b active also - very fast

Can run it on a phone then? Seems like it could be somewhat useful for people with poor eyesight or blindness

In terms of size yes, but I think it needs some work to get the model in the right format

couple people got it running on a raspberry pi though

Re: Moondream 3 Preview: Frontier-level reasoning at a blazing speed

#9
post #7

Moondream 2 has been very useful for me: I've been using it to automatically label object detection datasets for novel classes and distill an orders of magnitude smaller but similarly accurate CNN. One oddity is that I haven't seen the claimed improvements beyond the 2025-01-09 tag - subsequent releases improve recall but degrade precision pretty significantly. It'd be amazing if object detection VLMs like this repor…

Also used it for auto-labeling - it's crazy good for that
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