SAMSUNG ELECTRONICS CO., LTD. 750XGK
Geekbench AI Score
3017
Single Precision Score
4183
Half Precision Score
6633
Quantized Score
Geekbench AI 1.4.0 for Windows AVX2
Result Information
| User | harsidh |
| Upload Date | July 08 2025 01:06 PM |
| Views | 7 |
System Information
| AI Information | |
|---|---|
| Framework | OpenVINO |
| Backend | GPU |
| Device | Intel(R) UHD Graphics (iGPU) |
| System Information | |
|---|---|
| Operating System | Microsoft Windows 11 Home Single Language (64-bit) |
| Model | SAMSUNG ELECTRONICS CO., LTD. 750XGK |
| Motherboard | SAMSUNG ELECTRONICS CO., LTD. NP750XGJ-LG4IN |
| Power Plan | Samsung Mode |
| CPU Information | |
|---|---|
| Name | Intel Core i3-1315U |
| Topology | 1 Processor, 6 Cores, 8 Threads |
| Identifier | GenuineIntel Family 6 Model 186 Stepping 3 |
| Base Frequency | 1.20 GHz |
| Cluster 1 | 2 Cores |
| Cluster 2 | 4 Cores |
| Memory Information | |
|---|---|
| Size | 8.00 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
1529
284.3 IPS |
|
|
Image Classification (HP)
|
100% |
2321
431.6 IPS |
|
|
Image Classification (Q)
|
99% |
3218
600.2 IPS |
|
|
Image Segmentation (SP)
|
100% |
2846
46.1 IPS |
|
|
Image Segmentation (HP)
|
100% |
4361
70.7 IPS |
|
|
Image Segmentation (Q)
|
99% |
6234
101.0 IPS |
|
|
Pose Estimation (SP)
|
100% |
6045
7.05 IPS |
|
|
Pose Estimation (HP)
|
99% |
4441
5.18 IPS |
|
|
Pose Estimation (Q)
|
97% |
19830
23.2 IPS |
|
|
Object Detection (SP)
|
100% |
1765
140.0 IPS |
|
|
Object Detection (HP)
|
100% |
2576
204.3 IPS |
|
|
Object Detection (Q)
|
90% |
3899
311.7 IPS |
|
|
Face Detection (SP)
|
100% |
5342
63.5 IPS |
|
|
Face Detection (HP)
|
100% |
8436
100.2 IPS |
|
|
Face Detection (Q)
|
100% |
12669
150.5 IPS |
|
|
Depth Estimation (SP)
|
100% |
6382
49.2 IPS |
|
|
Depth Estimation (HP)
|
98% |
10131
78.3 IPS |
|
|
Depth Estimation (Q)
|
89% |
14282
111.1 IPS |
|
|
Style Transfer (SP)
|
100% |
15648
20.1 IPS |
|
|
Style Transfer (HP)
|
100% |
25081
32.2 IPS |
|
|
Style Transfer (Q)
|
98% |
43605
56.2 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
2630
97.1 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
3996
147.6 IPS |
|
|
Image Super-Resolution (Q)
|
99% |
8009
296.6 IPS |
|
|
Text Classification (SP)
|
71% |
934
1.35 KIPS |
|
|
Text Classification (HP)
|
71% |
1014
1.47 KIPS |
|
|
Text Classification (Q)
|
92% |
1026
1.38 KIPS |
|
|
Machine Translation (SP)
|
100% |
1029
17.7 IPS |
|
|
Machine Translation (HP)
|
98% |
1631
28.2 IPS |
|
|
Machine Translation (Q)
|
98% |
1641
28.4 IPS |
