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Chip comparison

Biren BR100 vs NVIDIA A10 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.

FieldBiren BR100NVIDIA A10 Tensor Core GPU
Process nodeTSMC N7Samsung 8N
Transistors (B)7728.3
Die size628 mm²
TDP550 W150 W
Memory64 GB HBM2e24 GB GDDR6
Memory bandwidth2,300 GB/s600 GB/s
FP16 (dense)1,024 TFLOPS125 TFLOPS
BF16 (dense)1,024 TFLOPS125 TFLOPS
INT8 (dense)2,048 TOPS250 TOPS
Form factorOAMPCIe
Announced2022-08-092021-04-12
Released2021-04-12

Robots running Biren BR100

No robots publicly running it yet.

Robots running NVIDIA A10 Tensor Core GPU

No robots publicly running it yet.

Data centers with Biren BR100

No data centers publicly running it yet.

Data centers with NVIDIA A10 Tensor Core GPU

No data centers publicly running it yet.

Common questions

Biren BR100 vs NVIDIA A10 Tensor Core GPU: which is faster for training?

Biren BR100 has 8.19x the dense FP16/BF16 throughput of the other (Biren BR100: 1,024 TFLOPS; NVIDIA A10 Tensor Core GPU: 125 TFLOPS). Real-world training speed also depends on memory bandwidth, interconnect, and software stack: see the spec diff for those inputs.

Biren BR100 vs NVIDIA A10 Tensor Core GPU: which has more memory?

Biren BR100 carries more HBM (Biren BR100: 64 GB HBM2e; NVIDIA A10 Tensor Core GPU: 24 GB GDDR6). Memory capacity sets the largest model that fits on one chip without partitioning; memory bandwidth sets inference throughput.

Biren BR100 vs NVIDIA A10 Tensor Core GPU: which is more power-efficient?

Dense FP16/BF16 TFLOPS per watt: Biren BR100 1.86 (1,024 ÷ 550 W); NVIDIA A10 Tensor Core GPU 0.83 (125 ÷ 150 W). Biren BR100 wins at the die level; system-level efficiency also depends on cooling and interconnect.

See also: every chip comparison · Biren BR100 full page · NVIDIA A10 Tensor Core GPU full page.