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Chip comparison

NVIDIA T4 Tensor Core GPU vs Tenstorrent Blackhole

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 Blackhole
Process nodeTSMC 12FFNTSMC N6
Transistors (B)13.6
Die size545 mm²
TDP70 W300 W
Memory16 GB GDDR632 GB GDDR6
Memory bandwidth320 GB/s512 GB/s
FP16 (dense)65 TFLOPS745 TFLOPS
INT8 (dense)130 TOPS2,980 TOPS
Form factorPCIe (single-slot, low-profile)PCIe
Announced2018-09-132024-07-01
Released2019-01-012025-01-01

Robots running NVIDIA T4 Tensor Core GPU

No robots publicly running it yet.

Robots running Tenstorrent Blackhole

No robots publicly running it yet.

Data centers with NVIDIA T4 Tensor Core GPU

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Data centers with Tenstorrent Blackhole

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Common questions

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

Tenstorrent Blackhole has 11.46x the dense FP16/BF16 throughput of the other (NVIDIA T4 Tensor Core GPU: 65 TFLOPS; Tenstorrent Blackhole: 745 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 Blackhole: which has more memory?

Tenstorrent Blackhole carries more HBM (NVIDIA T4 Tensor Core GPU: 16 GB GDDR6; Tenstorrent Blackhole: 32 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 Blackhole: which is more power-efficient?

Dense FP16/BF16 TFLOPS per watt: NVIDIA T4 Tensor Core GPU 0.93 (65 ÷ 70 W); Tenstorrent Blackhole 2.48 (745 ÷ 300 W). Tenstorrent Blackhole 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 Blackhole full page.