Compare · GPUs & AI chips
Blackwell B200 SXM vs Trainium2
RANKED BY DENSE FP16/BF16 TENSOR TFLOPS PER CHIP
#3 VS #12
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); Trainium2 ranks #12 (667 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 12 of 20
Dense FP16/BF16 tensor TFLOPS per chip
667 TFLOPS
MakerAWS
Date2024
Verified04 Sept 2026
Evidence
AWS Neuron Trainium2 Architecture page, compute table: each Trainium2 chip delivers "667 BF16/FP16/TF32 TFLOPS" dense; sparse counterpart is 2,563 TFLOPS and was not used. 96 GiB device memory. Trn2 instances are generally available (AWS announcement 3 Dec 2024).Try another pair
More Blackwell B200 SXM matchups
- Blackwell B200 SXM vs Instinct MI355X
- Blackwell B200 SXM vs Instinct MI350X
- Blackwell B200 SXM vs Blackwell Ultra B300 SXM
- Blackwell B200 SXM vs Gaudi 3
- Blackwell B200 SXM vs Instinct MI325X
- Blackwell B200 SXM vs Instinct MI300X
- Blackwell B200 SXM vs H200 SXM
- Blackwell B200 SXM vs H100 SXM
- Blackwell B200 SXM vs Instinct MI300A
- Blackwell B200 SXM vs TPU v6e (Trillium)
- Blackwell B200 SXM vs TPU v5p
- Blackwell B200 SXM vs Gaudi 2
Source Vendor product pages and official spec documents (AMD Instinct MI355X / MI350X / MI325X / MI300X / MI300A / MI250X / MI250 / MI210; NVIDIA…
Last checked 06 Sept 2026