DEPLOYDatabase

Chip comparison

Biren BR100 vs Google TPU v4

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 BR100Google TPU v4
Process nodeTSMC N7TSMC N7
Transistors (B)77
TDP550 W192 W
Memory64 GB HBM2e32 GB HBM2
Memory bandwidth2,300 GB/s1,200 GB/s
FP16 (dense)1,024 TFLOPS
BF16 (dense)1,024 TFLOPS275 TFLOPS
INT8 (dense)2,048 TOPS275 TOPS
Form factorOAMOAM (per-chip in v4 pod)
Announced2022-08-092021-05-18
Released2022-05-01

Robots running Biren BR100

No robots publicly running it yet.

Robots running Google TPU v4

No robots publicly running it yet.

Data centers with Biren BR100

No data centers publicly running it yet.

Common questions

Biren BR100 vs Google TPU v4: which is faster for training?

Biren BR100 has 3.72x the dense FP16/BF16 throughput of the other (Biren BR100: 1,024 TFLOPS; Google TPU v4: 275 TFLOPS). Real-world training speed also depends on memory bandwidth, interconnect, and software stack: see the spec diff for those inputs.

Biren BR100 vs Google TPU v4: which has more memory?

Biren BR100 carries more HBM (Biren BR100: 64 GB HBM2e; Google TPU v4: 32 GB HBM2). Memory capacity sets the largest model that fits on one chip without partitioning; memory bandwidth sets inference throughput.

Biren BR100 vs Google TPU v4: which is more power-efficient?

Dense FP16/BF16 TFLOPS per watt: Biren BR100 1.86 (1,024 ÷ 550 W); Google TPU v4 1.43 (275 ÷ 192 W). Biren BR100 wins at the die level; system-level efficiency also depends on cooling and interconnect.

Biren BR100 vs Google TPU v4: which is more widely used?

Biren BR100: 0 robots and 0 data centers publicly running it. Google TPU v4: 0 robots and 2 data centers. Empty here means no operator has said publicly, not zero adoption in the market.

See also: every chip comparison · Biren BR100 full page · Google TPU v4 full page.