SAMSUNG ELECTRONICS CO., LTD. 750QFG
Geekbench AI Score
4663
Single Precision Score
6493
Half Precision Score
10027
Quantized Score
Geekbench AI 1.3.0 for Windows AVX2
Result Information
| User | BengtC |
| Upload Date | April 19 2025 09:55 AM |
| Views | 5 |
System Information
| AI Information | |
|---|---|
| Framework | OpenVINO |
| Backend | GPU |
| Device | Intel(R) Iris(R) Xe Graphics (iGPU) |
| System Information | |
|---|---|
| Operating System | Microsoft Windows 11 Pro (64-bit) |
| Model | SAMSUNG ELECTRONICS CO., LTD. 750QFG |
| Motherboard | SAMSUNG ELECTRONICS CO., LTD. NP750QFG-KA5SE |
| Power Plan | SAMSUNG MODE |
| CPU Information | |
|---|---|
| Name | Intel Core i7-1360P |
| Topology | 1 Processor, 12 Cores, 16 Threads |
| Identifier | GenuineIntel Family 6 Model 186 Stepping 2 |
| Base Frequency | 2.20 GHz |
| Cluster 1 | 4 Cores |
| Cluster 2 | 8 Cores |
| Memory Information | |
|---|---|
| Size | 16.00 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
3005
558.8 IPS |
|
|
Image Classification (HP)
|
100% |
4766
886.4 IPS |
|
|
Image Classification (Q)
|
99% |
6738
1.26 KIPS |
|
|
Image Segmentation (SP)
|
100% |
4835
78.4 IPS |
|
|
Image Segmentation (HP)
|
100% |
7617
123.5 IPS |
|
|
Image Segmentation (Q)
|
99% |
10165
164.8 IPS |
|
|
Pose Estimation (SP)
|
100% |
9360
10.9 IPS |
|
|
Pose Estimation (HP)
|
99% |
7046
8.22 IPS |
|
|
Pose Estimation (Q)
|
97% |
28711
33.6 IPS |
|
|
Object Detection (SP)
|
100% |
2695
213.8 IPS |
|
|
Object Detection (HP)
|
100% |
4033
319.9 IPS |
|
|
Object Detection (Q)
|
90% |
6041
483.0 IPS |
|
|
Face Detection (SP)
|
100% |
7416
88.1 IPS |
|
|
Face Detection (HP)
|
100% |
10892
129.4 IPS |
|
|
Face Detection (Q)
|
100% |
16884
200.6 IPS |
|
|
Depth Estimation (SP)
|
100% |
9182
70.7 IPS |
|
|
Depth Estimation (HP)
|
98% |
15399
119.0 IPS |
|
|
Depth Estimation (Q)
|
89% |
20530
159.6 IPS |
|
|
Style Transfer (SP)
|
100% |
24677
31.7 IPS |
|
|
Style Transfer (HP)
|
100% |
40094
51.5 IPS |
|
|
Style Transfer (Q)
|
98% |
70594
91.0 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
4197
155.0 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
6816
251.7 IPS |
|
|
Image Super-Resolution (Q)
|
99% |
12745
472.0 IPS |
|
|
Text Classification (SP)
|
71% |
1341
1.94 KIPS |
|
|
Text Classification (HP)
|
71% |
1487
2.15 KIPS |
|
|
Text Classification (Q)
|
92% |
1517
2.04 KIPS |
|
|
Machine Translation (SP)
|
100% |
1404
24.2 IPS |
|
|
Machine Translation (HP)
|
96% |
1897
32.8 IPS |
|
|
Machine Translation (Q)
|
100% |
1828
31.5 IPS |
