Unverified50% confidenceFactExact time
相比BF16，FP8能将模型权重和计算数据量减半，理论上可将矩阵乘法内存带宽需求降低50%，并在支持FP8 Tensor Core的GPU上获得2倍以上计算吞吐量提升
1
Sources
50%
Confidence
Long-term
Relevance
7/12/2026
First Seen
Sources
LingBot-Video 1.3B Selective FP8 Quantization Benchmark: 22% Faster Sampling
redditr/comfyui7/11/2026
Related Claims
UnverifiedFP8相比BF16可提供约2倍的内存带宽节省和更高的矩阵计算吞吐81% similarVerifiedFP8 quantization technology reduces memory usage by approximately 50% with almost no loss in precision by compressing weights into an 8-bit representation.76% similarUnverifiedQuantization technology from FP32 to INT8 can reduce memory usage by approximately 75%.74% similarUnverifiedFP4 相对 FP16 可节省75%存储，采用每组16或32个权重共享一个 FP8 缩放因子的分组量化策略70% similar
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