Template:NvidiaDgxAccelerators
Appearance
Starting from P100,[1][2][3] to V100,[4] to A100,[5] to H100,[6] to B200[7][8] and to R100;[9] the comparison of accelerators used in DGX:
General & Architecture
[edit]| Model | Architecture | Socket | GPU | Fabrication Process | Transistor count
(billion) |
Die size
(mm2) |
Launched |
|---|---|---|---|---|---|---|---|
| P100 | Pascal | SXM/SXM2 | GP100 | TSMC 16FF+ | 15.3 | 610 | Q2 2016 |
| V100 16GB | Volta | SXM2 | GV100 | TSMC 12FFN | 21.1 | 815 | Q3 2017 |
| V100 32GB | SXM3 | ||||||
| A100 40GB | Ampere | SXM4 | GA100 | TSMC N7 | 54.2 | 826 | Q1 2020 |
| A100 80GB | Q4 2020 | ||||||
| H100 | Hopper | SXM5 | GH100 | TSMC 4N | 80 | 814 | Q3 2022 |
| H200 | Q3 2023 | ||||||
| B100 | Blackwell | SXM6 | GB100 | TSMC 4NP | 208 | N/A | Q4 2024 |
| B200 | |||||||
| R100 | Rubin | SXM7 | N/a | TSMC 3N | 338 | N/a | H2 2026 |
Cores, Clock & Power
[edit]| Model | Boost clock
(MHz) |
#SM | Cores
(FP32 CUDA) |
Cores
(FP64 excl. tensor) |
Cores
(Mixed INT32/FP32) |
Cores
(INT32) |
TDP
(W) |
|---|---|---|---|---|---|---|---|
| P100 | 1480 | 56 | 3584 | 1792 | N/a | N/a | 300 |
| V100 16GB | 1530 | 80 | 5120 | 2560 | N/A | 5120 | 300 |
| V100 32GB | 350 | ||||||
| A100 40GB | 1410 | 108 | 6912 | 3456 | 6912 | N/A | 400 |
| A100 80GB | |||||||
| H100 | 1980 | 132 | 16896 | 4608 | 16896 | N/A | 700 |
| H200 | 1000 | ||||||
| B100 | N/a | N/a | N/a | N/a | N/a | N/a | 700 |
| B200 | N/a | N/a | N/a | N/a | N/a | N/a | 1000 |
| R100 | N/a | N/a | N/a | N/a | N/a | N/a | 2300 |
Memory & Cache
[edit]| Model | Memory Type
(HBM) |
VRAM Size
(GB) |
Memory Speed
(Gb/s) |
Bus width
(bits) |
Bandwidth
(TB/s) |
L1 Cache
Per SM (KB) |
L1 Cache
Total (KB) |
L2 Cache
(KB) |
|---|---|---|---|---|---|---|---|---|
| P100 | HBM2 | 16 | 1.4 | 4096 | 0.72 | 24 | 1344 | 4096 |
| V100 16GB | HBM2 | 16 | 1.75 | 4096 | 0.9 | 128 | 10240 | 6144 |
| V100 32GB | 32 | |||||||
| A100 40GB | HBM2 | 40 | 2.4 | 5120 | 1.52 | 192 | 20736 | 40960 |
| A100 80GB | HBM2e | 80 | 3.2 | |||||
| H100 | HBM3 | 80 | 5.2 | 5120 | 3.35 | 192 | 25344 | 51200 |
| H200 | HBM3e | 141 | 6.3 | 6144 | 4.8 | |||
| B100 | HBM3e | 192 | 8 | 8192 | 8 | N/A | N/A | N/A |
| B200 | ||||||||
| R100 | HBM4 | N/a | N/a | N/a | N/a | N/a | N/a | N/a |
Compute Performance, Interconnect & Networking
[edit]| Model | FP32
(TFLOPS) |
FP64
(TFLOPS) |
INT8
dense tensor |
FP16
dense tensor |
bfloat16
dense tensor |
TF32
dense tensor |
FP64
dense tensor |
Interconnect
(NVLink; TB/s) |
Networking |
|---|---|---|---|---|---|---|---|---|---|
| P100 | 10.6 | 5.3 | N/a | 21.2 | N/a | N/a | N/a | 0.16 | ConnectX-4
(100 Gb/s) |
| V100 16GB | 15.7 | 7.8 | N/A | 125 TFLOPS | N/A | N/A | N/A | 0.3 | ConnectX-5
(100 Gb/s) |
| V100 32GB | |||||||||
| A100 40GB | 19.5 | 9.7 | 624 TOPS | 312 TFLOPS | 312 TFLOPS | 156 TFLOPS | 19.5 TFLOPS | 0.6 | ConnectX-6
(200 Gb/s) |
| A100 80GB | |||||||||
| H100 | 67 | 34 | 1.98 POPS | 990 TFLOPS | 990 TFLOPS | 495 TFLOPS | 67 TFLOPS | 0.9 | ConnectX-7
(400 Gb/s) |
| H200 | |||||||||
| B100 | N/a | N/a | 3.5 POPS | 1.98 PFLOPS | 1.98 PFLOPS | 989 TFLOPS | 30 TFLOPS | 1.8 | ConnectX-7
(400 Gb/s) |
| B200 | N/a | N/a | 4.5 POPS | 2.25 PFLOPS | 2.25 PFLOPS | 1.2 PFLOPS | 40 TFLOPS | ||
| R100 | N/a | N/a | N/a | N/a | N/a | N/a | N/a | N/a | ConnectX-9
(1600 Gb/s) |
| This template's documentation is missing, inadequate, or does not accurately describe its functionality or the parameters in its code. Please help add, expand, or improve it. |
- ^ "NVIDIA Tesla P100". Nvidia.
- ^ "NVIDIA Tesla P100 SXM2". TechPowerUp.
- ^ "NVIDIA Tesla P100 PCIe 16 GB". TechPowerUp.
- ^ Garreffa, Anthony (September 17, 2017). "NVIDIA Tesla V100 Tested: Near Unbelievable GPU Power". TweakTown.com. Retrieved December 30, 2025.
- ^ Smith, Ryan (May 14, 2020). "NVIDIA Ampere Unleashed: NVIDIA Announces New GPU Architecture, A100 GPU, and Accelerator". AnandTech. Archived from the original on July 29, 2024.
- ^ Smith, Ryan (March 22, 2022). "NVIDIA Hopper GPU Architecture and H100 Accelerator Announced: Working Smarter and Harder". AnandTech. Archived from the original on September 23, 2023.
- ^ "B100 vs B200: Which NVIDIA blackwell GPU is right for your AI workloads? | Blog — Northflank". Northflank — Deploy any project in seconds, in our cloud or yours. Retrieved 2026-06-15.
- ^ "Comparing Blackwell vs Hopper | B200 & B100 vs H200 & H100 | Exxact Blog". www.exxactcorp.com. Retrieved 2026-06-15.
- ^ Mitrasish; Co-founder; CTO; Spheron. "NVIDIA Rubin R100 GPU Chip Specs: Architecture, VRAM, and Cloud Availability (2026) | Spheron Blog". Spheron. Retrieved 2026-06-13.