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Chip comparison

AWS Inferentia 2 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.

FieldAWS Inferentia 2NVIDIA T4 Tensor Core GPU
Process nodeTSMC N7TSMC 12FFN
Transistors (B)13.6
Die size545 mm²
TDP250 W70 W
Memory32 GB HBM316 GB GDDR6
Memory bandwidth820 GB/s320 GB/s
FP16 (dense)65 TFLOPS
BF16 (dense)190 TFLOPS
FP8 (dense)380 TFLOPS
INT8 (dense)130 TOPS
Form factorInf2 EC2 instancePCIe (single-slot, low-profile)
Announced2022-12-012018-09-13
Released2023-04-012019-01-01

Robots running AWS Inferentia 2

No robots publicly running it yet.

Robots running NVIDIA T4 Tensor Core GPU

No robots publicly running it yet.

Data centers with AWS Inferentia 2

No data centers publicly running it yet.

Data centers with NVIDIA T4 Tensor Core GPU

No data centers publicly running it yet.

Common questions

AWS Inferentia 2 vs NVIDIA T4 Tensor Core GPU: which is faster for training?

AWS Inferentia 2 has 5.85x the dense FP16/BF16 throughput of the other (AWS Inferentia 2: 380 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.

AWS Inferentia 2 vs NVIDIA T4 Tensor Core GPU: which has more memory?

AWS Inferentia 2 carries more HBM (AWS Inferentia 2: 32 GB HBM3; 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.

AWS Inferentia 2 vs NVIDIA T4 Tensor Core GPU: which is more power-efficient?

Dense FP16/BF16 TFLOPS per watt: AWS Inferentia 2 1.52 (380 ÷ 250 W); NVIDIA T4 Tensor Core GPU 0.93 (65 ÷ 70 W). AWS Inferentia 2 wins at the die level; system-level efficiency also depends on cooling and interconnect.

See also: every chip comparison · AWS Inferentia 2 full page · NVIDIA T4 Tensor Core GPU full page.