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Chip comparison

NVIDIA A10 Tensor Core GPU vs NVIDIA T4 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 A10 Tensor Core GPUNVIDIA T4 Tensor Core GPU
Process nodeSamsung 8NTSMC 12FFN
Transistors (B)28.313.6
Die size628 mm²545 mm²
TDP150 W70 W
Memory24 GB GDDR616 GB GDDR6
Memory bandwidth600 GB/s320 GB/s
FP16 (dense)125 TFLOPS65 TFLOPS
BF16 (dense)125 TFLOPS
INT8 (dense)250 TOPS130 TOPS
Form factorPCIePCIe (single-slot, low-profile)
Announced2021-04-122018-09-13
Released2021-04-122019-01-01

Robots running NVIDIA A10 Tensor Core GPU

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Robots running NVIDIA T4 Tensor Core GPU

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Data centers with NVIDIA A10 Tensor Core GPU

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Data centers with NVIDIA T4 Tensor Core GPU

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Common questions

NVIDIA A10 Tensor Core GPU vs NVIDIA T4 Tensor Core GPU: which is faster for training?

NVIDIA A10 Tensor Core GPU has 1.92x the dense FP16/BF16 throughput of the other (NVIDIA A10 Tensor Core GPU: 125 TFLOPS; NVIDIA T4 Tensor Core GPU: 65 TFLOPS). Real-world training speed also depends on memory bandwidth, interconnect, and software stack: see the spec diff for those inputs.

NVIDIA A10 Tensor Core GPU vs NVIDIA T4 Tensor Core GPU: which has more memory?

NVIDIA A10 Tensor Core GPU carries more HBM (NVIDIA A10 Tensor Core GPU: 24 GB GDDR6; NVIDIA T4 Tensor Core GPU: 16 GB GDDR6). Memory capacity sets the largest model that fits on one chip without partitioning; memory bandwidth sets inference throughput.

NVIDIA A10 Tensor Core GPU vs NVIDIA T4 Tensor Core GPU: which is more power-efficient?

Dense FP16/BF16 TFLOPS per watt: NVIDIA A10 Tensor Core GPU 0.83 (125 ÷ 150 W); NVIDIA T4 Tensor Core GPU 0.93 (65 ÷ 70 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 A10 Tensor Core GPU full page · NVIDIA T4 Tensor Core GPU full page.