HONOR FMB-P
Geekbench ML Score
4107
ONNX CPU Inference Score
Geekbench ML 0.6.0 for Windows AVX2
Result Information
| Upload Date | June 18 2025 10:36 AM |
| Views | 4 |
System Information
| System Information | |
|---|---|
| Operating System | Microsoft Windows 11 Home (64-bit) |
| Model | HONOR FMB-P |
| Motherboard | HONOR FMB-P-PCB |
| Power Plan | Balanced |
| CPU Information | |
|---|---|
| Name | Intel(R) Core(TM) Ultra 9 285H |
| Topology | 1 Processor, 16 Cores |
| Identifier | GenuineIntel Family 6 Model 197 Stepping 2 |
| Base Frequency | 2.90 GHz |
| Cluster 1 | 6 Cores |
| Cluster 2 | 10 Cores |
| L1 Instruction Cache | 64.0 KB x 8 |
| L1 Data Cache | 48.0 KB x 8 |
| L2 Cache | 3.00 MB x 2 |
| L3 Cache | 24.0 MB x 1 |
| Memory Information | |
|---|---|
| Size | 32.00 GB |
| Inference Information | |
|---|---|
| Framework | ONNX |
| Backend | CPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
2218
415.0 IPS |
|
|
Image Classification (F16)
|
100% |
2104
393.8 IPS |
|
|
Image Classification (I8)
|
99% |
3526
659.7 IPS |
|
|
Image Segmentation (F32)
|
100% |
1850
30.9 IPS |
|
|
Image Segmentation (F16)
|
100% |
1780
29.7 IPS |
|
|
Image Segmentation (I8)
|
98% |
3165
52.9 IPS |
|
|
Pose Estimation (F32)
|
100% |
7607
9.21 IPS |
|
|
Pose Estimation (F16)
|
100% |
7515
9.10 IPS |
|
|
Pose Estimation (I8)
|
100% |
26943
32.6 IPS |
|
|
Object Detection (F32)
|
100% |
2091
156.1 IPS |
|
|
Object Detection (F16)
|
100% |
1970
147.1 IPS |
|
|
Object Detection (I8)
|
62% |
1637
122.2 IPS |
|
|
Face Detection (F32)
|
100% |
4418
52.5 IPS |
|
|
Face Detection (F16)
|
100% |
4376
52.0 IPS |
|
|
Face Detection (I8)
|
89% |
4511
53.6 IPS |
|
|
Depth Estimation (F32)
|
100% |
7878
61.1 IPS |
|
|
Depth Estimation (F16)
|
100% |
7926
61.5 IPS |
|
|
Depth Estimation (I8)
|
96% |
14715
114.1 IPS |
|
|
Style Transfer (F32)
|
100% |
17043
22.4 IPS |
|
|
Style Transfer (F16)
|
100% |
16765
22.1 IPS |
|
|
Style Transfer (I8)
|
98% |
24422
32.1 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
3347
119.5 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
3370
120.4 IPS |
|
|
Image Super-Resolution (I8)
|
99% |
5755
205.5 IPS |
|
|
Text Classification (F32)
|
100% |
1240
1.78 KIPS |
|
|
Text Classification (F16)
|
100% |
1189
1.71 KIPS |
|
|
Text Classification (I8)
|
98% |
1210
1.74 KIPS |
|
|
Machine Translation (F32)
|
100% |
2363
43.5 IPS |
|
|
Machine Translation (F16)
|
100% |
2305
42.4 IPS |
|
|
Machine Translation (I8)
|
67% |
4079
75.1 IPS |
