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0 pointsyeldarb1d ago0 comments

It’s a big improvement if you’re already paying them but, given their aggressive approach to licensing, I can’t imagine why anyone would choose to use an Ultralytics model on a new project in 2026. You’re just asking to be shaken down and have to pay off a large bill down the line.

RF-DETR is both faster and more accurate and truly open source with an Apache 2.0 license: https://github.com/roboflow/rf-detr

Full disclosure: I’m one of the co-founders of Roboflow (we made RF-DETR, wrote this blog post, and are a sub-licensor of Ultralytics’ models.)

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MrGLaDOS1d ago· 3 in thread

“RF-DETR is both faster and more accurate and truly open source with an Apache 2.0 license”

Misleading marketing statement.

The catch is that for image resolutions >=700x700pixels (most production usecases), the roboflow license is actually PML1.0 instead of Apache2.0 https://github.com/roboflow/rf-detr#license

yeldarbOP17h ago

That may be true for legacy CNNs but very few production use-cases require such a large resolution with DETRs. The latency scales quadratically with the resolution.

Regardless, you can do whatever resolution you want with the Apache 2.0 model. Just change the config at runtime; it was trained to be resolution agnostic.

You are correct that we also released larger models with a larger backbone under a different, non open-source license.

krapht1d ago

> The catch is that for image resolutions >=700x700pixels (most production usecases)

Citation needed? 2XL looks like you go up to 800x800 pixel inputs. This isn't the dealbreaker you say it is - all pipelines benefit from thoughtful crop and rescaling before going to inference.

MrGLaDOS1d ago

See the url in my comment (search for the term rfdetr-2xlarge). 2XL does indeed go up to 800x800 and has PML1.0 license instead of apache 2.0.

Rescaling is fine for some purposes but but not for all. For many domain-specific (often less common and odd dimensioned) objects, downscaling will severely reduce recall. There is a reason that Roboflow slaps a license that is not open source on those specific architectures.

In some cases tiled inferencing (for example with https://github.com/obss/sahi ) might do the job.

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