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Chip comparison

AWS Inferentia 2 vs NVIDIA B100 (Blackwell)

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.

FieldAWS Inferentia 2NVIDIA B100 (Blackwell)
Process nodeTSMC N7TSMC 4NP
TDP250 W700 W
Memory32 GB HBM3192 GB HBM3e
Memory bandwidth820 GB/s8,000 GB/s
FP16 (dense)—1,750 TFLOPS
BF16 (dense)190 TFLOPS1,750 TFLOPS
FP8 (dense)380 TFLOPS3,500 TFLOPS
Form factorInf2 EC2 instanceSXM6 (700 W envelope)
Announced2022-12-012024-03-18
Released2023-04-012024-11-01

Robots running AWS Inferentia 2

No robots publicly running it yet.

Robots running NVIDIA B100 (Blackwell)

No robots publicly running it yet.

Data centers with AWS Inferentia 2

No data centers publicly running it yet.

Data centers with NVIDIA B100 (Blackwell)

No data centers publicly running it yet.

Common questions

AWS Inferentia 2 vs NVIDIA B100 (Blackwell): which is faster for training?

NVIDIA B100 (Blackwell) has 9.21x the dense FP8 throughput of the other (AWS Inferentia 2: 380 TFLOPS; NVIDIA B100 (Blackwell): 3,500 TFLOPS). Real-world training speed also depends on memory bandwidth, interconnect, and software stack: see the spec diff for those inputs.

AWS Inferentia 2 vs NVIDIA B100 (Blackwell): which has more memory?

NVIDIA B100 (Blackwell) carries more HBM (AWS Inferentia 2: 32 GB HBM3; NVIDIA B100 (Blackwell): 192 GB HBM3e). Memory capacity sets the largest model that fits on one chip without partitioning; memory bandwidth sets inference throughput.

AWS Inferentia 2 vs NVIDIA B100 (Blackwell): which is more power-efficient?

Dense FP8 TFLOPS per watt: AWS Inferentia 2 1.52 (380 ÷ 250 W); NVIDIA B100 (Blackwell) 5.00 (3,500 ÷ 700 W). NVIDIA B100 (Blackwell) wins at the die level; system-level efficiency also depends on cooling and interconnect.

See also: every chip comparison · AWS Inferentia 2 full page · NVIDIA B100 (Blackwell) full page.