ICL Techno F160a
Geekbench AI Score
2878
Single Precision Score
3841
Half Precision Score
2165
Quantized Score
Geekbench AI 1.5.0 for Windows AVX2
Result Information
| Upload Date | September 21 2025 08:56 AM |
| Views | 3 |
System Information
| AI Information | |
|---|---|
| Framework | ONNX |
| Backend | DirectML |
| Device | AMD Radeon(TM) Graphics |
| 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% |
1074
199.6 IPS |
|
|
Image Classification (HP)
|
100% |
1367
254.1 IPS |
|
|
Image Classification (Q)
|
100% |
985
183.2 IPS |
|
|
Image Segmentation (SP)
|
100% |
1339
21.7 IPS |
|
|
Image Segmentation (HP)
|
100% |
1693
27.4 IPS |
|
|
Image Segmentation (Q)
|
98% |
1138
18.5 IPS |
|
|
Pose Estimation (SP)
|
100% |
11618
13.6 IPS |
|
|
Pose Estimation (HP)
|
100% |
20782
24.2 IPS |
|
|
Pose Estimation (Q)
|
96% |
9414
11.0 IPS |
|
|
Object Detection (SP)
|
100% |
1310
103.9 IPS |
|
|
Object Detection (HP)
|
100% |
1613
128.0 IPS |
|
|
Object Detection (Q)
|
88% |
1162
93.2 IPS |
|
|
Face Detection (SP)
|
100% |
2785
33.1 IPS |
|
|
Face Detection (HP)
|
100% |
3714
44.1 IPS |
|
|
Face Detection (Q)
|
97% |
2311
27.6 IPS |
|
|
Depth Estimation (SP)
|
100% |
6613
50.9 IPS |
|
|
Depth Estimation (HP)
|
99% |
9801
75.5 IPS |
|
|
Depth Estimation (Q)
|
77% |
5060
40.4 IPS |
|
|
Style Transfer (SP)
|
100% |
20178
25.9 IPS |
|
|
Style Transfer (HP)
|
100% |
33248
42.7 IPS |
|
|
Style Transfer (Q)
|
98% |
15867
20.5 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
3926
145.0 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
5689
210.1 IPS |
|
|
Image Super-Resolution (Q)
|
99% |
2728
101.0 IPS |
|
|
Text Classification (SP)
|
100% |
829
1.11 KIPS |
|
|
Text Classification (HP)
|
100% |
850
1.13 KIPS |
|
|
Text Classification (Q)
|
97% |
535
717.3 IPS |
|
|
Machine Translation (SP)
|
100% |
1474
25.4 IPS |
|
|
Machine Translation (HP)
|
100% |
1540
26.5 IPS |
|
|
Machine Translation (Q)
|
70% |
683
12.8 IPS |
