Unverified50% confidenceFactExact time
扩散模型（如Stable Diffusion）通过逐步去噪还原图像，擅长细节纹理；自回归多模态模型（如GPT Image 2）在理解复杂文字指令和保持角色一致性方面更具优势
1
Sources
50%
Confidence
Long-term
Relevance
7/20/2026
First Seen
Sources
Related Claims
Verified扩散模型以 DALL-E 2、Stable Diffusion、Midjourney 为代表，重新定义了图像生成任务78% similarVerifiedStable Diffusion is based on the Latent Diffusion Model and generates high-quality images by performing a denoising process in a compressed latent space77% similarUnverifiedText in images generated by early diffusion models such as Stable Diffusion and DALL-E 2 often appeared garbled or blurry.76% similarUnverifiedIn autoregressive models such as GPT-Image-2, the word order and structure of the prompt are more important than in diffusion models, because the model processes tokens sequentially and earlier descriptions tend to receive higher attention weights.75% similarUnverifiedIn diffusion model image-to-image or reference-image-guided generation, the signal-to-noise ratio of the input image directly affects the detail fidelity and style transfer accuracy of the output.74% similar
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