DS-086 125U Default string Default string
Geekbench AI Score
4236
Single Precision Score
6675
Half Precision Score
10066
Quantized Score
Geekbench AI 1.3.0 for Windows AVX2
Result Information
| User | shaneGH |
| Upload Date | June 27 2025 06:29 AM |
| Views | 10 |
System Information
| AI Information | |
|---|---|
| Framework | OpenVINO |
| Backend | GPU |
| Device | Intel(R) Graphics (iGPU) |
| System Information | |
|---|---|
| Operating System | Microsoft Windows 11 IoT Enterprise LTSC (64-bit) |
| Model | Default string Default string |
| Motherboard | Default string Default string |
| Power Plan | High performance |
| CPU Information | |
|---|---|
| Name | Intel(R) Core(TM) Ultra 5 125U |
| Topology | 1 Processor, 12 Cores, 14 Threads |
| Identifier | GenuineIntel Family 6 Model 170 Stepping 4 |
| Base Frequency | 3.60 GHz |
| Cluster 1 | 2 Cores |
| Cluster 2 | 10 Cores |
| Memory Information | |
|---|---|
| Size | 16.00 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
2912
541.5 IPS |
|
|
Image Classification (HP)
|
100% |
4398
818.0 IPS |
|
|
Image Classification (Q)
|
100% |
5985
1.11 KIPS |
|
|
Image Segmentation (SP)
|
100% |
3141
50.9 IPS |
|
|
Image Segmentation (HP)
|
100% |
6910
112.0 IPS |
|
|
Image Segmentation (Q)
|
99% |
9548
154.8 IPS |
|
|
Pose Estimation (SP)
|
100% |
8715
10.2 IPS |
|
|
Pose Estimation (HP)
|
99% |
8108
9.49 IPS |
|
|
Pose Estimation (Q)
|
97% |
26288
30.8 IPS |
|
|
Object Detection (SP)
|
100% |
2608
206.8 IPS |
|
|
Object Detection (HP)
|
100% |
4269
338.6 IPS |
|
|
Object Detection (Q)
|
88% |
6936
555.9 IPS |
|
|
Face Detection (SP)
|
100% |
6379
75.8 IPS |
|
|
Face Detection (HP)
|
100% |
12017
142.8 IPS |
|
|
Face Detection (Q)
|
100% |
17942
213.2 IPS |
|
|
Depth Estimation (SP)
|
100% |
9004
69.4 IPS |
|
|
Depth Estimation (HP)
|
98% |
16648
128.7 IPS |
|
|
Depth Estimation (Q)
|
89% |
18389
142.9 IPS |
|
|
Style Transfer (SP)
|
100% |
21350
27.4 IPS |
|
|
Style Transfer (HP)
|
100% |
29909
38.4 IPS |
|
|
Style Transfer (Q)
|
98% |
61389
79.2 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
3799
140.3 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
6788
250.7 IPS |
|
|
Image Super-Resolution (Q)
|
99% |
10983
406.8 IPS |
|
|
Text Classification (SP)
|
71% |
1180
1.71 KIPS |
|
|
Text Classification (HP)
|
71% |
1747
2.53 KIPS |
|
|
Text Classification (Q)
|
92% |
1982
2.66 KIPS |
|
|
Machine Translation (SP)
|
100% |
1629
28.1 IPS |
|
|
Machine Translation (HP)
|
96% |
2355
40.7 IPS |
|
|
Machine Translation (Q)
|
100% |
2325
40.0 IPS |
