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On 2026-04-23 @sainingxie claimed that, for the first time, a single generalist…
Brief
Saining Xie argues that after several years of incremental progress, a single generalist image model (tweeted 2026-04-23) now beats specialized systems like SAM3 and DepthAnything3. He attributes this to image-editing pretraining, which he claims lets dense labeling tasks be reframed as simpler post-training steps instead of long, bespoke engineering efforts.
Why it matters
On 2026-04-23 @sainingxie claimed that, for the first time, a single generalist image model is outperforming top domain-specific models including SAM3 and DepthAnything3.
Key details
- @sainingxie argues that image-editing as a pretraining paradigm makes dense labeling problems solvable via post-training, replacing years of complex, domain-specific training recipes with scalable general pretraining.