BudgetPix: adaptive tokenization matches full-compute pixel diffusion with 25% of the compute
_akhaliq · x · 2026-10-13
BudgetPix proposes compute-adaptive tokenization for pixel-space image diffusion: an entropy-guided quadtree encoder emits variable-length tokens based on visual complexity, a scale-aware decoder reconstructs images, and a flexible training/sampling schedule lets one checkpoint run across budgets. It matches MiniT2I-L at 512² and PixelDiT at 1024² with just 25% of the original compute, and hits near-zero quality loss on MeanFlow class-conditional generation with 60% compute (FID +0.8). Human and VLM evals confirm a better quality-efficiency tradeoff than prior budget-adaptive baselines.
More from Multimodal
- Surreal AI image series "Sometimes, we need fire" goes viral — gizakdag · 2026-10-13
- Antonio Banderas to star in AI-powered feature 'Cortés' from Utopai Studios, now shooting in Paris — lmoroney · 2026-10-13
- Minimax H3 Refmod workflow: character-consistent video from photos plus a voice sample, no LoRA training — AlsterwasserHH · 2026-10-13
- An indie game ad made entirely with Google Flow and Suno — ahmettnq · 2026-10-13
- AI-generated Assassin's Creed Ethiopia-style action short — Dear_Hovercraft_6500 · 2026-10-13
- User makes Upanishads two-birds animated short with Claude Opus beyond coding — selfawareatom · 2026-10-13