Unverified60% confidenceBenchmarkExact time
The NVIDIA A100's theoretical FP16 peak compute is approximately 312 TFLOPS, but GPU utilization in naive LLM inference scenarios is often below 30%.
2
Sources
60%
Confidence
Long-term
Relevance
7/11/2026
First Seen
Sources
Related Claims
VerifiedThe NVIDIA H100 single-card FP64 double-precision floating-point performance reaches approximately 34 TFLOPS.82% similarUnverifiedThe NVIDIA H100's FP16 peak can reach 1000 TFLOPS, but when training Transformer models the MFU is typically only 30%–60%.79% similarUnverifiedAt FP16 half-precision computation, the RTX 4090 has a theoretical performance of approximately 330 TFLOPS, while the M2 Ultra's GPU delivers approximately 27.2 TFLOPS.76% similarVerifiedThe NVIDIA H20's peak BF16 compute is approximately 296 TFLOPS, significantly reduced compared to the H100's 989 TFLOPS, but it retains 141 GB HBM3 memory and 4.0 TB/s memory bandwidth.76% similarUnverifiedThe T4 GPU has 16GB of VRAM and 8.1 TFLOPS of FP32 compute performance.74% similar
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