Opus 5.5 explains image token density over banjo music
The author used Opus 5.5 to generate a video explaining that a 1080p image equals 2961 tokens and the visual preprocessing decisions involved.
a quick peak into model & tokenization internals a 1080p picture is worth 2961 "words" (to glm-flash-5.3) every time you send in an image to a model, the harness makes a preprocessing decision how to resize and convert it into tokens good to internalize how token dense images and video are, especially at high frame rates/resolutions also think about compaction! what does it even mean to compact an image? you cant rewrite an image, the harness has to pick which to keep in context, which to pass references to, which to ignore all of this is a harness design decision when you see really low eval scores on visual tasks, sometimes models are blind because preprocessing distorts fine-grained image details. sometimes they just suck at perception. in both cases it's worth looking at what they actually "see" this time opus 5.5 set the vid to banjo music