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Chip comparison

NVIDIA A100 Tensor Core GPU vs Tenstorrent Wormhole

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 A100 Tensor Core GPUTenstorrent Wormhole
Process nodeTSMC N7GlobalFoundries 12nm
Transistors (B)54
Die size826 mm²
TDP400 W160 W
Memory80 GB HBM2e12 GB GDDR6
Memory bandwidth2,039 GB/s288 GB/s
FP16 (dense)312 TFLOPS148 TFLOPS
BF16 (dense)312 TFLOPS
INT8 (dense)624 TOPS590 TOPS
Launch price (list)$10,000
Form factorSXM4PCIe (n300, n150)
Announced2020-05-142024-07-01
Released2020-05-142024-08-01

Robots running NVIDIA A100 Tensor Core GPU

No robots publicly running it yet.

Robots running Tenstorrent Wormhole

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Data centers with NVIDIA A100 Tensor Core GPU

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Data centers with Tenstorrent Wormhole

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Common questions

NVIDIA A100 Tensor Core GPU vs Tenstorrent Wormhole: which is faster for training?

NVIDIA A100 Tensor Core GPU has 2.11x the dense FP16/BF16 throughput of the other (NVIDIA A100 Tensor Core GPU: 312 TFLOPS; Tenstorrent Wormhole: 148 TFLOPS). Real-world training speed also depends on memory bandwidth, interconnect, and software stack: see the spec diff for those inputs.

NVIDIA A100 Tensor Core GPU vs Tenstorrent Wormhole: which has more memory?

NVIDIA A100 Tensor Core GPU carries more HBM (NVIDIA A100 Tensor Core GPU: 80 GB HBM2e; Tenstorrent Wormhole: 12 GB GDDR6). Memory capacity sets the largest model that fits on one chip without partitioning; memory bandwidth sets inference throughput.

NVIDIA A100 Tensor Core GPU vs Tenstorrent Wormhole: which is more power-efficient?

Dense FP16/BF16 TFLOPS per watt: NVIDIA A100 Tensor Core GPU 0.78 (312 ÷ 400 W); Tenstorrent Wormhole 0.93 (148 ÷ 160 W). Tenstorrent Wormhole wins at the die level; system-level efficiency also depends on cooling and interconnect.

See also: every chip comparison · NVIDIA A100 Tensor Core GPU full page · Tenstorrent Wormhole full page.