Tim Simmons examines anonymous Polaris outputs across portrait motion, action scenes, text rendering and physically complex prompts. The model often preserves a convincing cinematic look, but its results vary sharply between generations and can lose continuity when movement becomes complicated.
Tim Simmons finds Vega especially strong at multilingual speech, facial detail and synchronized dialogue. The tests also expose recurring limits in object permanence, background continuity and prompt adherence, so the anonymous leaderboard scores do not replace direct testing for a creator's intended shots.
Tim Simmons then demonstrates a reference-driven workflow in Stills Lab. Shot metadata and visual search help creators find useful cinematic examples, extract lighting and composition ideas, and convert those references into structured prompts without copying the original image itself.
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