Unverified50% confidenceFactExact time

扩散模型的迭代去噪过程对数值误差敏感，每步的微小误差会累积并影响最终图像，采样步数越多量化误差影响越大

1

Sources

50%

Confidence

Long-term

Relevance

7/10/2026

First Seen

Sources

Krea2实测：FP8与BF16画质差距还存在吗？

redditr/StableDiffusion7/9/2026

Related Claims

Unverified扩散模型的推理是迭代去噪过程，通常需要数十甚至数百个时间步，对数值误差格外敏感84% similar Unverified批次归一化层在小批次场景下统计量估计噪声很大，与Dice损失的区域级计算特性叠加会放大预测概率分布的波动79% similar Verified模型的泛化误差等于偏差平方加方差加不可约噪声79% similar Unverified自回归生成的误差累积效应源于模型只能沿单一路径前进，误差以乘积形式放大78% similar Verified扩散模型通过逐步去噪从随机噪声中还原目标图像或视频帧，通常需要数十步去噪迭代，计算开销极大78% similar

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