Samsung SAMSUNG ELECTRONICS CO., LTD. 960XFH
Geekbench AI Score
3062
Single Precision Score
3090
Half Precision Score
1882
Quantized Score
Geekbench AI 1.1.0 for Windows AVX2
Result Information
| User | Wolfgang1756 |
| Upload Date | December 26 2024 01:18 AM |
| Views | 3 |
System Information
| AI Information | |
|---|---|
| Framework | ONNX |
| Backend | DirectML |
| Device | Intel(R) Iris(R) Xe Graphics |
| System Information | |
|---|---|
| Operating System | Microsoft Windows 11 Enterprise (64-bit) |
| Model | SAMSUNG ELECTRONICS CO., LTD. 960XFH |
| Motherboard | SAMSUNG ELECTRONICS CO., LTD. NP960XFH-XA3US |
| Power Plan | Balanced |
| CPU Information | |
|---|---|
| Name | Intel Core i9-13900H |
| Topology | 1 Processor, 14 Cores, 20 Threads |
| Identifier | GenuineIntel Family 6 Model 186 Stepping 2 |
| Base Frequency | 2.60 GHz |
| Cluster 1 | 6 Cores |
| Cluster 2 | 8 Cores |
| Memory Information | |
|---|---|
| Size | 32.00 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
1265
235.3 IPS |
|
|
Image Classification (HP)
|
100% |
1381
256.8 IPS |
|
|
Image Classification (Q)
|
99% |
1016
189.5 IPS |
|
|
Image Segmentation (SP)
|
100% |
2134
34.6 IPS |
|
|
Image Segmentation (HP)
|
100% |
2426
39.3 IPS |
|
|
Image Segmentation (Q)
|
98% |
1542
25.1 IPS |
|
|
Pose Estimation (SP)
|
100% |
13283
15.5 IPS |
|
|
Pose Estimation (HP)
|
100% |
13269
15.5 IPS |
|
|
Pose Estimation (Q)
|
96% |
6576
7.71 IPS |
|
|
Object Detection (SP)
|
100% |
1410
111.8 IPS |
|
|
Object Detection (HP)
|
98% |
1297
103.2 IPS |
|
|
Object Detection (Q)
|
89% |
1106
88.5 IPS |
|
|
Face Detection (SP)
|
100% |
2857
33.9 IPS |
|
|
Face Detection (HP)
|
100% |
3302
39.2 IPS |
|
|
Face Detection (Q)
|
97% |
1926
23.0 IPS |
|
|
Depth Estimation (SP)
|
100% |
6231
48.0 IPS |
|
|
Depth Estimation (HP)
|
98% |
6718
51.9 IPS |
|
|
Depth Estimation (Q)
|
76% |
4233
34.0 IPS |
|
|
Style Transfer (SP)
|
100% |
27567
35.4 IPS |
|
|
Style Transfer (HP)
|
100% |
34812
44.8 IPS |
|
|
Style Transfer (Q)
|
98% |
17590
22.7 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
3566
131.7 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
5025
185.6 IPS |
|
|
Image Super-Resolution (Q)
|
99% |
1570
58.1 IPS |
|
|
Text Classification (SP)
|
100% |
971
1.30 KIPS |
|
|
Text Classification (HP)
|
100% |
423
564.5 IPS |
|
|
Text Classification (Q)
|
97% |
508
680.9 IPS |
|
|
Machine Translation (SP)
|
100% |
846
14.6 IPS |
|
|
Machine Translation (HP)
|
100% |
839
14.5 IPS |
|
|
Machine Translation (Q)
|
60% |
428
9.55 IPS |
