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Chip comparison

AWS Trainium 2 vs NVIDIA H200 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 Trainium 2NVIDIA H200 Tensor Core GPU
Process nodeTSMC N5TSMC 4N
Transistors (B)80
Die size814 mm²
TDP500 W700 W
Memory96 GB HBM3141 GB HBM3e
Memory bandwidth2,900 GB/s4,800 GB/s
FP16 (dense)989 TFLOPS
BF16 (dense)667 TFLOPS989 TFLOPS
FP8 (dense)1,300 TFLOPS1,979 TFLOPS
INT8 (dense)1,300 TOPS1,979 TOPS
Form factorAWS Neuron 2 (Trn2 UltraServer with 64 chips per unit)SXM5
Announced2024-12-032023-11-13
Released2025-01-012024-03-01

Robots running AWS Trainium 2

No robots publicly running it yet.

Robots running NVIDIA H200 Tensor Core GPU

No robots publicly running it yet.

Common questions

AWS Trainium 2 vs NVIDIA H200 Tensor Core GPU: which is faster for training?

NVIDIA H200 Tensor Core GPU has 1.52x the dense FP8 throughput of the other (AWS Trainium 2: 1,300 TFLOPS; NVIDIA H200 Tensor Core GPU: 1,979 TFLOPS). Real-world training speed also depends on memory bandwidth, interconnect, and software stack: see the spec diff for those inputs.

AWS Trainium 2 vs NVIDIA H200 Tensor Core GPU: which has more memory?

NVIDIA H200 Tensor Core GPU carries more HBM (AWS Trainium 2: 96 GB HBM3; NVIDIA H200 Tensor Core GPU: 141 GB HBM3e). Memory capacity sets the largest model that fits on one chip without partitioning; memory bandwidth sets inference throughput.

AWS Trainium 2 vs NVIDIA H200 Tensor Core GPU: which is more power-efficient?

Dense FP8 TFLOPS per watt: AWS Trainium 2 2.60 (1,300 ÷ 500 W); NVIDIA H200 Tensor Core GPU 2.83 (1,979 ÷ 700 W). NVIDIA H200 Tensor Core GPU wins at the die level; system-level efficiency also depends on cooling and interconnect.

AWS Trainium 2 vs NVIDIA H200 Tensor Core GPU: which is more widely used?

AWS Trainium 2: 0 robots and 3 data centers publicly running it. NVIDIA H200 Tensor Core GPU: 0 robots and 4 data centers. Empty here means no operator has said publicly, not zero adoption in the market.

See also: every chip comparison · AWS Trainium 2 full page · NVIDIA H200 Tensor Core GPU full page.