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Chip comparison

NVIDIA T4 Tensor Core GPU vs NVIDIA V100 Tensor Core GPU

Side-by-side specs

Straight from each vendor's datasheet. Winner in bold: higher throughput, memory, or transistor count; lower power draw or price. Sparse (2:4) throughput roughly doubles the FP8/INT8 numbers shown.

FieldNVIDIA T4 Tensor Core GPUNVIDIA V100 Tensor Core GPU
Process nodeTSMC 12FFNTSMC 12FFN
Transistors (B)13.621.1
Die size545 mm²815 mm²
TDP70 W300 W
Memory16 GB GDDR632 GB HBM2
Memory bandwidth320 GB/s900 GB/s
FP16 (dense)65 TFLOPS125 TFLOPS
INT8 (dense)130 TOPS
Form factorPCIe (single-slot, low-profile)SXM2 / PCIe
Announced2018-09-132017-05-10
Released2019-01-012017-12-01

Robots running NVIDIA T4 Tensor Core GPU

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Robots running NVIDIA V100 Tensor Core GPU

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Data centers with NVIDIA T4 Tensor Core GPU

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Data centers with NVIDIA V100 Tensor Core GPU

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Common questions

NVIDIA T4 Tensor Core GPU vs NVIDIA V100 Tensor Core GPU: which is faster for training?

NVIDIA V100 Tensor Core GPU has 1.92x the dense FP16/BF16 throughput of the other (NVIDIA T4 Tensor Core GPU: 65 TFLOPS; NVIDIA V100 Tensor Core GPU: 125 TFLOPS). Real-world training speed also depends on memory bandwidth, interconnect, and software stack: see the spec diff for those inputs.

NVIDIA T4 Tensor Core GPU vs NVIDIA V100 Tensor Core GPU: which has more memory?

NVIDIA V100 Tensor Core GPU carries more HBM (NVIDIA T4 Tensor Core GPU: 16 GB GDDR6; NVIDIA V100 Tensor Core GPU: 32 GB HBM2). Memory capacity sets the largest model that fits on one chip without partitioning; memory bandwidth sets inference throughput.

NVIDIA T4 Tensor Core GPU vs NVIDIA V100 Tensor Core GPU: which is more power-efficient?

Dense FP16/BF16 TFLOPS per watt: NVIDIA T4 Tensor Core GPU 0.93 (65 ÷ 70 W); NVIDIA V100 Tensor Core GPU 0.42 (125 ÷ 300 W). NVIDIA T4 Tensor Core GPU wins at the die level; system-level efficiency also depends on cooling and interconnect.

See also: every chip comparison · NVIDIA T4 Tensor Core GPU full page · NVIDIA V100 Tensor Core GPU full page.