Unverified50% confidenceFactExact time
Diffusion models require tens or even hundreds of forward inference passes to generate each frame
1
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50%
Confidence
Long-term
Relevance
9/18/2026
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UnverifiedThe denoising process of diffusion models typically requires tens to hundreds of iterations (called sampling steps), each of which requires a complete forward pass through the neural network.75% similarUnverifiedWhen model scale crosses from billions of parameters to the hundreds-of-billions level, non-linear emergent capability jumps manifest on code tasks.74% similarUnverified大模型在约千亿参数规模附近突然展现出思维链推理、多步数学解题等此前小模型不具备的能力74% similarUnverifiedAutoregressive model inference must be executed strictly in serial; generating each token requires one complete forward pass, which is an important structural reason for the high cost of large model inference.73% similarUnverifiedDiffusion models typically require tens to thousands of inference steps, and each step is a global operation on the entire image, generally implemented using U-Net or DiT architectures.73% similar
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