ICL Techno F160a
Geekbench AI Score
2185
Single Precision Score
995
Half Precision Score
2448
Quantized Score
Geekbench AI 1.5.0 for Windows AVX2
Result Information
| Upload Date | September 21 2025 08:52 AM |
| Views | 2 |
System Information
| AI Information | |
|---|---|
| Framework | ONNX |
| Backend | CPU |
| Device | AMD Ryzen 7 5700U |
| System Information | |
|---|---|
| Operating System | Windows 11 (64-bit) |
| Model | ICL Techno F160a |
| Motherboard | ICL Techno F160a |
| CPU Information | |
|---|---|
| Name | AMD Ryzen 7 5700U |
| Topology | 1 Processor, 8 Cores, 16 Threads |
| Identifier | AuthenticAMD Family 23 Model 104 Stepping 1 |
| Base Frequency | 1.80 GHz |
| Cluster 1 | 8 Cores |
| Memory Information | |
|---|---|
| Size | 32.00 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
2065
384.0 IPS |
|
|
Image Classification (HP)
|
100% |
402
74.7 IPS |
|
|
Image Classification (Q)
|
96% |
2376
443.8 IPS |
|
|
Image Segmentation (SP)
|
100% |
584
9.47 IPS |
|
|
Image Segmentation (HP)
|
100% |
467
7.57 IPS |
|
|
Image Segmentation (Q)
|
97% |
2287
37.2 IPS |
|
|
Pose Estimation (SP)
|
100% |
4783
5.58 IPS |
|
|
Pose Estimation (HP)
|
100% |
3764
4.39 IPS |
|
|
Pose Estimation (Q)
|
86% |
5843
6.91 IPS |
|
|
Object Detection (SP)
|
100% |
1938
153.8 IPS |
|
|
Object Detection (HP)
|
100% |
506
40.1 IPS |
|
|
Object Detection (Q)
|
58% |
1519
165.9 IPS |
|
|
Face Detection (SP)
|
100% |
3217
38.2 IPS |
|
|
Face Detection (HP)
|
100% |
1026
12.2 IPS |
|
|
Face Detection (Q)
|
96% |
4483
53.5 IPS |
|
|
Depth Estimation (SP)
|
100% |
4748
36.6 IPS |
|
|
Depth Estimation (HP)
|
99% |
1453
11.2 IPS |
|
|
Depth Estimation (Q)
|
78% |
5402
43.1 IPS |
|
|
Style Transfer (SP)
|
100% |
8598
11.1 IPS |
|
|
Style Transfer (HP)
|
100% |
6472
8.32 IPS |
|
|
Style Transfer (Q)
|
87% |
9135
11.9 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
1341
49.5 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
1039
38.4 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
1847
68.4 IPS |
|
|
Text Classification (SP)
|
100% |
1033
1.38 KIPS |
|
|
Text Classification (HP)
|
100% |
473
630.9 IPS |
|
|
Text Classification (Q)
|
97% |
328
438.9 IPS |
|
|
Machine Translation (SP)
|
100% |
1222
21.1 IPS |
|
|
Machine Translation (HP)
|
100% |
565
9.73 IPS |
|
|
Machine Translation (Q)
|
68% |
1196
23.1 IPS |
