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Chip comparison

NVIDIA H100 Tensor Core GPU 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.

FieldNVIDIA H100 Tensor Core GPUNVIDIA H200 Tensor Core GPU
Process nodeTSMC 4NTSMC 4N
Transistors (B)8080
Die size814 mm²814 mm²
TDP700 W700 W
Memory80 GB HBM3141 GB HBM3e
Memory bandwidth3,350 GB/s4,800 GB/s
FP16 (dense)989 TFLOPS989 TFLOPS
BF16 (dense)989 TFLOPS989 TFLOPS
FP8 (dense)1,979 TFLOPS1,979 TFLOPS
INT8 (dense)1,979 TOPS1,979 TOPS
Launch price (list)$30,000
Form factorSXM5SXM5
Announced2022-03-222023-11-13
Released2022-10-132024-03-01

Robots running NVIDIA H100 Tensor Core GPU

No robots publicly running it yet.

Robots running NVIDIA H200 Tensor Core GPU

No robots publicly running it yet.

Common questions

NVIDIA H100 Tensor Core GPU vs NVIDIA H200 Tensor Core GPU: which is faster for training?

NVIDIA H200 Tensor Core GPU has 1.00x the dense FP8 throughput of the other (NVIDIA H100 Tensor Core GPU: 1,979 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.

NVIDIA H100 Tensor Core GPU vs NVIDIA H200 Tensor Core GPU: which has more memory?

NVIDIA H200 Tensor Core GPU carries more HBM (NVIDIA H100 Tensor Core GPU: 80 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.

NVIDIA H100 Tensor Core GPU vs NVIDIA H200 Tensor Core GPU: which is more power-efficient?

Dense FP8 TFLOPS per watt: NVIDIA H100 Tensor Core GPU 2.83 (1,979 ÷ 700 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.

NVIDIA H100 Tensor Core GPU vs NVIDIA H200 Tensor Core GPU: which is more widely used?

NVIDIA H100 Tensor Core GPU: 0 robots and 7 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 · NVIDIA H100 Tensor Core GPU full page · NVIDIA H200 Tensor Core GPU full page.