Intel X99
Geekbench AI Score
5783
Single Precision Score
6174
Half Precision Score
4312
Quantized Score
Geekbench AI 1.2.0 for Windows AVX2
Result Information
| User | TiggerTH |
| Upload Date | December 16 2024 05:18 PM |
| Views | 16 |
System Information
| AI Information | |
|---|---|
| Framework | ONNX |
| Backend | DirectML |
| Device | Radeon RX 570 Series |
| System Information | |
|---|---|
| Operating System | Microsoft Windows 10 Pro (64-bit) |
| Model | Intel X99 |
| Motherboard | Intel X99H |
| Power Plan | Bitsum Highest Performance |
| CPU Information | |
|---|---|
| Name | Intel Xeon E5-2670 v3 |
| Topology | 1 Processor, 12 Cores, 24 Threads |
| Identifier | GenuineIntel Family 6 Model 63 Stepping 2 |
| Base Frequency | 2.30 GHz |
| Cluster 1 | 12 Cores |
| Memory Information | |
|---|---|
| Size | 24.00 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
2516
467.8 IPS |
|
|
Image Classification (HP)
|
100% |
2845
529.1 IPS |
|
|
Image Classification (Q)
|
100% |
2105
391.4 IPS |
|
|
Image Segmentation (SP)
|
100% |
2966
48.1 IPS |
|
|
Image Segmentation (HP)
|
100% |
3155
51.2 IPS |
|
|
Image Segmentation (Q)
|
98% |
2475
40.2 IPS |
|
|
Pose Estimation (SP)
|
100% |
29548
34.5 IPS |
|
|
Pose Estimation (HP)
|
100% |
32599
38.0 IPS |
|
|
Pose Estimation (Q)
|
96% |
25865
30.3 IPS |
|
|
Object Detection (SP)
|
100% |
2858
226.7 IPS |
|
|
Object Detection (HP)
|
100% |
2685
212.9 IPS |
|
|
Object Detection (Q)
|
88% |
2347
188.1 IPS |
|
|
Face Detection (SP)
|
100% |
7283
86.5 IPS |
|
|
Face Detection (HP)
|
100% |
9220
109.6 IPS |
|
|
Face Detection (Q)
|
97% |
5805
69.2 IPS |
|
|
Depth Estimation (SP)
|
100% |
15224
117.3 IPS |
|
|
Depth Estimation (HP)
|
99% |
17255
133.3 IPS |
|
|
Depth Estimation (Q)
|
77% |
11113
89.1 IPS |
|
|
Style Transfer (SP)
|
100% |
53339
68.6 IPS |
|
|
Style Transfer (HP)
|
100% |
58766
75.5 IPS |
|
|
Style Transfer (Q)
|
98% |
43379
55.9 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
8833
326.2 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
9866
364.3 IPS |
|
|
Image Super-Resolution (Q)
|
99% |
5696
210.9 IPS |
|
|
Text Classification (SP)
|
100% |
998
1.33 KIPS |
|
|
Text Classification (HP)
|
100% |
762
1.02 KIPS |
|
|
Text Classification (Q)
|
97% |
609
816.4 IPS |
|
|
Machine Translation (SP)
|
100% |
1275
22.0 IPS |
|
|
Machine Translation (HP)
|
96% |
1458
25.2 IPS |
|
|
Machine Translation (Q)
|
70% |
725
13.6 IPS |
