Unverified50% confidenceFactExact time
Acceleration LoRAs use distillation training to enable video models to achieve near-original quality with fewer denoising steps, completing sampling in 3 to 4 steps, which can reduce inference time to approximately one-tenth of the original.
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50%
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Long-term
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9/18/2026
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UnverifiedDuring diffusion model inference, sampler algorithms typically require only 20 to 30 iterations to obtain high-quality image generation results, far fewer than the 1,000 steps used during training.71% similarUnverifiedStandard generation with traditional diffusion models typically requires 50–100 denoising iterations, whereas the Turbo version can reduce the steps to 4–8, achieving a speed improvement of more than 10x.70% similarUnverifiedThe host's own testing found that minimal mode completes tasks approximately one-third faster than standard mode, with results comparable to standard mode.67% similarUnverifiedLoRA微调只需训练不到1%的参数即可达到接近全参微调的效果，显存需求大幅降低至单张消费级显卡可承受范围66% similarUnverifiedWith the advancement of model distillation, consistency models, and inference acceleration technologies, the cost of video generation is expected to drop by an order of magnitude within the next 1–2 years.64% similar
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