Unverified70% confidenceFactExact time
TensorRT支持FP32/FP16/INT8/FP8多种精度校准
2
Sources
70%
Confidence
Long-term
Relevance
7/10/2026
First Seen
Sources
TensorRT多设备推理：突破单GPU显存瓶颈的工程实践
rss6/25/2026
Related Claims
Verified在配备 Tensor Core 的 NVIDIA GPU（如 A100、H100）上，FP16/BF16 矩阵运算的吞吐量可以达到 FP32 的 2-8 倍77% similarUnverifiedTensorRT-LLM内置对NVFP4等量化格式的端到端支持，包括量化权重自动解包、混合精度推理调度及算子融合优化75% similarUnverifiedV100的Tensor Core在FP16精度下峰值算力可达125 TFLOPS，是前代Pascal架构的5倍以上75% similarUnverifiedFP8是Blackwell架构原生支持的低精度计算格式，包含E4M3和E5M2两种变体，Tensor Core的FP8计算吞吐是FP16的两倍74% similarUnverifiedFP32到FP16的转换在现代GPU的Tensor Core上可实现2-4倍的吞吐量提升74% similar
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