HONOR FMB-P
Geekbench AI Score
6865
Single Precision Score
9510
Half Precision Score
4699
Quantized Score
Geekbench AI 1.5.0 for Windows AVX2
Result Information
| Upload Date | October 21 2025 02:03 PM |
| Views | 6 |
System Information
| AI Information | |
|---|---|
| Framework | ONNX |
| Backend | DirectML |
| Device | Intel(R) Arc(TM) 130T GPU (16GB) |
| System Information | |
|---|---|
| Operating System | Microsoft Windows 11 (64-bit) |
| Model | HONOR FMB-P |
| Motherboard | HONOR FMB-P-PCB |
| CPU Information | |
|---|---|
| Name | Intel(R) Core(TM) Ultra 5 225H |
| Topology | 1 Processor, 14 Cores |
| Identifier | GenuineIntel Family 6 Model 197 Stepping 2 |
| Base Frequency | 1.70 GHz |
| Cluster 1 | 4 Cores |
| Cluster 2 | 10 Cores |
| Memory Information | |
|---|---|
| Size | 32.00 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
4209
782.7 IPS |
|
|
Image Classification (HP)
|
100% |
4507
838.1 IPS |
|
|
Image Classification (Q)
|
99% |
2912
543.1 IPS |
|
|
Image Segmentation (SP)
|
100% |
5530
89.6 IPS |
|
|
Image Segmentation (HP)
|
100% |
8762
142.0 IPS |
|
|
Image Segmentation (Q)
|
98% |
4015
65.3 IPS |
|
|
Pose Estimation (SP)
|
100% |
18112
21.1 IPS |
|
|
Pose Estimation (HP)
|
100% |
33092
38.6 IPS |
|
|
Pose Estimation (Q)
|
96% |
15314
17.9 IPS |
|
|
Object Detection (SP)
|
100% |
4560
361.7 IPS |
|
|
Object Detection (HP)
|
100% |
5822
461.8 IPS |
|
|
Object Detection (Q)
|
87% |
3524
283.0 IPS |
|
|
Face Detection (SP)
|
100% |
8207
97.5 IPS |
|
|
Face Detection (HP)
|
100% |
12928
153.6 IPS |
|
|
Face Detection (Q)
|
97% |
5784
69.0 IPS |
|
|
Depth Estimation (SP)
|
100% |
14554
112.1 IPS |
|
|
Depth Estimation (HP)
|
99% |
22320
172.0 IPS |
|
|
Depth Estimation (Q)
|
77% |
11309
90.7 IPS |
|
|
Style Transfer (SP)
|
100% |
43980
56.5 IPS |
|
|
Style Transfer (HP)
|
100% |
67780
87.1 IPS |
|
|
Style Transfer (Q)
|
98% |
35269
45.5 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
8251
304.7 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
11487
424.2 IPS |
|
|
Image Super-Resolution (Q)
|
99% |
5404
200.1 IPS |
|
|
Text Classification (SP)
|
100% |
1105
1.48 KIPS |
|
|
Text Classification (HP)
|
100% |
1214
1.62 KIPS |
|
|
Text Classification (Q)
|
97% |
627
840.5 IPS |
|
|
Machine Translation (SP)
|
100% |
2526
43.5 IPS |
|
|
Machine Translation (HP)
|
100% |
2916
50.2 IPS |
|
|
Machine Translation (Q)
|
70% |
1065
20.0 IPS |
