Unverified50% confidenceTradeoffExact time
Video streams are continuously high-frequency data, and if a large model is called for inference on every frame, computational overhead and latency may become bottlenecks.
1
Sources
50%
Confidence
Long-term
Relevance
9/11/2026
First Seen
Sources
Related Entities
Related Claims
UnverifiedTechniques such as quantization, speculative decoding, and KV Cache optimization can reduce VLM latency by 30% to 60%, but still cannot meet the frame-level latency requirements of real-time video processing.72% 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.71% similar
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