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Chip comparison

NVIDIA T4 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 T4 Tensor Core GPUTenstorrent Wormhole
Process nodeTSMC 12FFNGlobalFoundries 12nm
Transistors (B)13.6
Die size545 mm²
TDP70 W160 W
Memory16 GB GDDR612 GB GDDR6
Memory bandwidth320 GB/s288 GB/s
FP16 (dense)65 TFLOPS148 TFLOPS
INT8 (dense)130 TOPS590 TOPS
Form factorPCIe (single-slot, low-profile)PCIe (n300, n150)
Announced2018-09-132024-07-01
Released2019-01-012024-08-01

Robots running NVIDIA T4 Tensor Core GPU

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Robots running Tenstorrent Wormhole

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Data centers with NVIDIA T4 Tensor Core GPU

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Data centers with Tenstorrent Wormhole

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Common questions

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

Tenstorrent Wormhole has 2.28x the dense FP16/BF16 throughput of the other (NVIDIA T4 Tensor Core GPU: 65 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 T4 Tensor Core GPU vs Tenstorrent Wormhole: which has more memory?

NVIDIA T4 Tensor Core GPU carries more HBM (NVIDIA T4 Tensor Core GPU: 16 GB GDDR6; Tenstorrent Wormhole: 12 GB GDDR6). Memory capacity sets the largest model that fits on one chip without partitioning; memory bandwidth sets inference throughput.

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

Dense FP16/BF16 TFLOPS per watt: NVIDIA T4 Tensor Core GPU 0.93 (65 ÷ 70 W); Tenstorrent Wormhole 0.93 (148 ÷ 160 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 T4 Tensor Core GPU full page · Tenstorrent Wormhole full page.