Compare · GPUs & AI chips
Blackwell B200 SXM vs A100 SXM 80GB
RANKED BY DENSE FP16/BF16 TENSOR TFLOPS PER CHIP
#3 VS #17
CHECKED 06 SEPT 2026
Side by side
Verdict
Blackwell B200 SXM ranks #3 of 20 on Dense FP16/BF16 tensor TFLOPS per chip (2.25 PFLOPS); A100 SXM 80GB ranks #17 (312 TFLOPS).
Rank 03 of 20 · leads
Dense FP16/BF16 tensor TFLOPS per chip
2.25 PFLOPS
MakerNVIDIA
Date2025
Verified04 Sept 2026
Evidence
NVIDIA HGX Platform page, HGX B200 row ("8x NVIDIA Blackwell SXM", footnote 4: "HGX B300 and HGX B200 shipping now"). FP16/BF16 Tensor Core is listed as 36 PFLOPS for the 8-GPU board. Footnote 2: dense is half the sparse spec. Dense board total is therefore 18 PFLOPS; per chip 18 / 8 = 2.25 PFLOPS. Total memory 1.4 TB => 180 GB HBM3E per SXM.Rank 17 of 20
Dense FP16/BF16 tensor TFLOPS per chip
312 TFLOPS
MakerNVIDIA
Date2020
Verified04 Sept 2026
Evidence
NVIDIA A100 product page, A100 80GB SXM column: FP16 Tensor Core 312 TFLOPS | 624 TFLOPS* and BFLOAT16 Tensor Core 312 TFLOPS | 624 TFLOPS*. Asterisk is "With sparsity". Dense figure used here is 312 TFLOPS. 80 GB HBM2e.Try another pair
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Source Vendor product pages and official spec documents (AMD Instinct MI355X / MI350X / MI325X / MI300X / MI300A / MI250X / MI250 / MI210; NVIDIA…
Last checked 06 Sept 2026