Verified75% confidenceTradeoffExact time
The more sampling steps a diffusion model uses, the more thorough the denoising and the higher the image quality, but the computational time also increases proportionally.
3
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75%
Confidence
Long-term
Relevance
8/26/2026
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Related Claims
UnverifiedThe number of iterative denoising steps is a tunable hyperparameter; more steps generally yield higher generation quality but take longer, while fewer steps are faster, providing a quality-efficiency trade-off.78% similarVerifiedDiffusion models restore target images or video frames from random noise through stepwise denoising, typically requiring dozens of denoising iterations, with extremely high computational overhead.77% similarUnverifiedWhen the intrinsic dimension d is large, exponentially more samples are needed to achieve the same accuracy.76% similarUnverifiedDiffusion language models often require dozens or even hundreds of denoising iterations to ensure generation quality, with each step requiring one complete forward pass, so the actual speed advantage is not always apparent.76% similarUnverified扩散模型步数越多理论上结果越精细，但耗时也成比例增长，20步是速度与质量的经典平衡点76% similar
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