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SkalskiP
@skalskip92
Open-source Lead @roboflow. VLMs. GPU poor. Dog person. Coffee addict. Dyslexic. | GH: | HF:
加入 February 2014
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SAM3 vs Astra for text-prompt segmentation SAM3 gives much more precise masks. it just often fails to understand complicated text prompts. Astra is great at language. it rarely misses what you want to detect, usually only when the task needs internal domain knowledge. masks come back as JSON, point by point. slower, and less accurate than SAM3 we just rolled out Astra segmentation in playground link: ↓ more Astra examples below
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Astra can do segmentation this is pure VLM result. no expert models (like SAM) were used No other VLM even comes close to this quality - high effort - avg input tokens / image: 2,052 - avg output tokens / image: 4,685 - avg cost / image: $0.255 - median time / image: 78.3 s ↓ GPT-6 Astra segmentation deep dive
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