Unverified50% confidenceBenchmarkExact time
The Tesla V100's FP16 compute performance is approximately 31.4 TFLOPS, and up to 125 TFLOPS with Tensor Cores enabled.
1
Sources
50%
Confidence
Long-term
Relevance
9/12/2026
First Seen
Sources
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Related Claims
UnverifiedThe Tesla V100's inference speed for running 8B-class models at FP16 precision is approximately in the range of 20–40 tokens/s.76% similarVerifiedThe NVIDIA H100 single-card FP64 double-precision floating-point performance reaches approximately 34 TFLOPS.75% similarUnverifiedA single TPU v4 chip has a peak compute of approximately 275 TFLOPS (BF16 precision), and a TPU v4-32 pod consists of 32 chips interconnected via ICI high-speed interconnects, with a total compute of approximately 8,800 TFLOPS.75% 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.74% 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.73% similar
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