面向深度学习用户的Nvidia各版本GPU参数汇总整理

做深度学习离不开算力,就像到达诗和远方的旅途离不开交通工具。本文面向深度学习用户整理市面上常用的各个版本GPU的关键参数,进行汇总整理,方便大家随时查阅。如果数据有误,或有新GPU问世,或者需要补充的参数维度,各位看官可以及时通过联系方式来找我更新数据。

注:仅统计Memory在 16GB以上、发售时间在2017年及以后、算力性能满足深度学习计算要求(Cuda算力性能>=7.0)的GPU。若表中单元格为空,则为暂无数据或数据待补充。博主将不定期移除上市时间最久、已停产过时、市面上已大量退役的GPU数据信息项。

(当前数据整理截止为2025年3月)

Tesla系列

版本型号MemoryCUDA CoreCUDA性能FP8/INT8
T(F)OPs
FP16
半精度TFLOPs
FP32
单精度TFLOPs
FP64
双精度TFLOPs
总线位宽总线带宽最大功率发布时间原价¥
B系B10096 GB *2
HBM3e
16896*24096位*28 TB/s700w
B系B200180GB
HBM3e
9P4.5P75377.7 TB/s1000w2024
H系H10080GB
HBM2e/HBM3
14592
16896
9.03341
3958
756.449
989.43
51.2
66.9
25.6
33.5
5120位2039GB/s350w
700w
2022.03.2226.4w
H系H200141GB
HBM3e
3341
3958
1671
1979
60
67
30
34
H系H80080GB
HBM2e/HBM3
184324P2P60342TB/s(HBM2e)
3.9TB/s(HBM3)
350w
700w
2023.03
H系H2096 GB
HBM3
2961484414.0 TB/s
L系L4048GB
GDDR6
181768.9362.06690.5161.414384位864GB/s300w2022.10.13
L系L2048GB
HBM3
10240239119.559.8NA384位864 GB/s
L系L424GB
GDDR6
74248.912130.30.49192位300GB/s72w2023.03.21
L系L219375w
A系A10040GB/80GB
HBM2
69128.031219.59.75120位1555GB/s250w2020.05.14
A系A80040GB/80GB
HBM2
6912124831219.59.71.6 TB/s400w2022.118.7w
A系A4048GB
GDDR6
107528.6149.6837.421.168384位695.8GB/s300w2020.10.05
A系A3024GB
HBM2
35848.0165.1210.325.1613072位933.1GB/s165w2021.04.12
A系A1024GB
GDDR6
92168.6124.9631.240.976384位600GB/s150w2021.04.12
A系A164*16GB
GDDR6
4*12808.64*18.4324*4.6081.08484*128位4*200GB/s250w2021.04.12
A系A216GB
GDDR6
12808.618.1244.5310.14128位200GB/s40-60w2021.11.10
T系T416GB
GDDR6
25607.564.88.1256位320GB/s70w2018.09.12
V系V10016GB/32GB
HBM2
51207.0119.192
112.224
105.680
14.899
14.028
13.210
7.450
7.014
6.605
4096位900GB/s
829.44GB/s
250w2017.05.10

GeForce系列

版本型号MemoryCUDA CoreCUDA性能FP8/INT8
T(F)OPs
FP16
半精度TFLOPs
FP32
单精度TFLOPs
FP64
双精度TFLOPs
显存位宽总线带宽最大功率发布时间原价¥
50系RTX 509032GB
GDDR7
21760
12.8
512位575w$1999
50系RTX 5090 D32 GB GDDR72176012.8512位1792GB/s575w16499
50系RTX 508016GB
GDDR7
1075212.8256位960GB/s360w8299
40系RTX 409024GB
GDDR6X
163848.982.5882.581.290384位1008GB/s450w2022
10.12
12999
40系RTX 4090D24GB145928.973.5473.541.149384位1008GB/s425w2023
12.28
11999
40系RTX 4080 Super16GB102408.951.351.30.802256位736GB/s320w2024
01.31
8099
40系RTX 408016GB97288.948.7448.740.762256位716.8GB/s320w2022
11.16
9499
40系RTX 4070 Ti Super16GB84488.944.144.10.689256位672GB/s285w2024
01.24
6499
30系RTX 3090 Ti24GB107528.633.54
39.99
33.54
39.99
0.524
0.625
384位1008GB/s450w2022
03.29
14999
30系RTX 309024GB104968.629.38
35.68
29.28
35.58
0.459
0.558
384位935.8GB/s350w2020
09.02
11999

Quadro系列

型号
MemoryCUDA CoreCUDA性能FP8/INT8
T(F)OPs
FP16
半精度TFLOPs
FP32
单精度TFLOPs
FP64
双精度TFLOPs
显存位宽总线带宽最大功率发布时间原价¥
RTX 600048GB
GDDR6
181768.991.1384位960GB/s300w
RTX 500032GB
GDDR6
250w
RTX 450024GB
GDDR6
210w
RTX 400020GB
GDDR6
130w
RTX 4000 SFF20GB
GDDR6
70w
RTX 200016GB
GDDR6
70w
RTX A600048GB
GDDR6
8.6300w
RTX A500024GB
GDDR6
8.6230w
RTX A450020GB
GDDR6
200w
RTX A400016GB
GDDR6
8.6140w
Quadro RTX 800048GB
GDDR6
7.5
Quadro RTX 600024GB
GDDR6
7.5
Quadro RTX 500016GB
GDDR6
7.5
Quadro GV10032GB
HBM2
7.0

参考来源

  1. https://www.nvidia.cn/geforce/graphics-cards/40-series/
  2. https://www.nvidia.com/en-us/geforce/graphics-cards/40-series/rtx-4090/
  3. https://www.nvidia.cn/geforce/graphics-cards/30-series/
  4. https://www.nvidia.cn/geforce/graphics-cards/compare/
  5. https://detail.zol.com.cn/1208/1207097/param.shtml
  6. https://developer.nvidia.com/cuda-gpus
  7. https://zh.wikipedia.org/wiki/NVIDIA_Tesla
  8. https://www.bilibili.com/read/cv33922816/
  9. https://zh.wikipedia.org/wiki/NVIDIA_GeForce_40%E7%B3%BB%E5%88%97
  10. https://zh.wikipedia.org/wiki/NVIDIA_GeForce_30%E7%B3%BB%E5%88%97
  11. https://zh.wikipedia.org/wiki/NVIDIA_GeForce_20%E7%B3%BB%E5%88%97
  12. https://zh.wikipedia.org/wiki/NVIDIA_GeForce_10%E7%B3%BB%E5%88%97
  13. https://ai.oldpan.me/t/topic/287
  14. https://en.wikipedia.org/wiki/GeForce_40_series
  15. https://www.nvidia.com/en-us/design-visualization/rtx-6000/
  16. https://www.nvidia.com/en-us/design-visualization/desktop-graphics/
  17. https://resources.nvidia.com/en-us-design-viz-stories-ep/l40-linecard?lx=CCKW39&&search=professional%20graphics
  18. https://www.nvidia.com/content/dam/en-zz/Solutions/design-visualization/quadro-product-literature/NV-DS-Quadro-M6000-24GB-US-NV-fnl-HR.pdf
  19. https://images.nvidia.com/content/pdf/quadro/data-sheets/192195-DS-NV-Quadro-P5000-US-12Sept-NV-FNL-WEB.pdf
  20. https://images.nvidia.com/content/pdf/quadro/data-sheets/192152-NV-DS-Quadro-P6000-US-12Sept-NV-FNL-WEB.pdf
  21. https://www.nvidia.com/content/dam/en-zz/Solutions/design-visualization/productspage/quadro/quadro-desktop/quadro-pascal-gp100-data-sheet-us-nv-704562-r1.pdf
  22. https://www.nvidia.com/content/dam/en-zz/Solutions/design-visualization/productspage/quadro/quadro-desktop/quadro-volta-gv100-data-sheet-us-nvidia-704619-r3-web.pdf
  23. https://www.nvidia.com/content/dam/en-zz/Solutions/design-visualization/quadro-product-literature/quadro-rtx-5000-data-sheet-us-nvidia-704120-r4-web.pdf
  24. https://www.nvidia.cn/design-visualization/rtx-5000/
  25. https://www.nvidia.com/content/dam/en-zz/Solutions/design-visualization/quadro-product-literature/quadro-rtx-6000-us-nvidia-704093-r4-web.pdf
  26. https://www.nvidia.com/content/dam/en-zz/Solutions/design-visualization/quadro-product-literature/quadro-rtx-8000-us-nvidia-946977-r1-web.pdf
  27. https://viperatech.com/shop/nvidia-hgx-h20/
  28. https://www.nvidia.com/en-us/data-center/h200/
  29. https://www.nvidia.com/en-us/data-center/h100/
  30. https://www.nvidia.cn/geforce/graphics-cards/50-series/rtx-5090-d/
  31. https://www.nvidia.cn/geforce/graphics-cards/50-series/rtx-5080/
  32. https://www.nvidia.com/en-us/geforce/graphics-cards/50-series/rtx-5090/
  33. https://www.nvidia.com/en-us/data-center/hgx/
  34. https://blog.csdn.net/Ai17316391579/article/details/132627201
  35. https://www.jb51.net/hardware/cpu/956950.html
  36. https://resources.nvidia.com/en-us-blackwell-architecture/datasheet
  37. https://www.techpowerup.com/gpu-specs/b100.c4275
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