HONOR FMB-P
Geekbench ML Score
6512
ONNX DirectML Inference Score
Geekbench ML 0.6.0 for Windows AVX2
Result Information
| Upload Date | June 18 2025 11:37 AM |
| Views | 2 |
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 | DirectML |
| Device | Intel(R) Arc(TM) 140T GPU (16GB) |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
4429
828.8 IPS |
|
|
Image Classification (F16)
|
100% |
4420
827.2 IPS |
|
|
Image Classification (I8)
|
100% |
3260
610.0 IPS |
|
|
Image Segmentation (F32)
|
100% |
5608
93.7 IPS |
|
|
Image Segmentation (F16)
|
100% |
5624
93.9 IPS |
|
|
Image Segmentation (I8)
|
98% |
3975
66.4 IPS |
|
|
Pose Estimation (F32)
|
100% |
21648
26.2 IPS |
|
|
Pose Estimation (F16)
|
100% |
21649
26.2 IPS |
|
|
Pose Estimation (I8)
|
100% |
18040
21.8 IPS |
|
|
Object Detection (F32)
|
100% |
4094
305.6 IPS |
|
|
Object Detection (F16)
|
100% |
3792
283.1 IPS |
|
|
Object Detection (I8)
|
59% |
2712
202.5 IPS |
|
|
Face Detection (F32)
|
100% |
7607
90.4 IPS |
|
|
Face Detection (F16)
|
100% |
7833
93.1 IPS |
|
|
Face Detection (I8)
|
89% |
4850
57.7 IPS |
|
|
Depth Estimation (F32)
|
100% |
17834
138.3 IPS |
|
|
Depth Estimation (F16)
|
100% |
18054
140.0 IPS |
|
|
Depth Estimation (I8)
|
95% |
13429
104.1 IPS |
|
|
Style Transfer (F32)
|
100% |
52252
68.7 IPS |
|
|
Style Transfer (F16)
|
100% |
54262
71.4 IPS |
|
|
Style Transfer (I8)
|
98% |
42943
56.5 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
9350
333.9 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
9552
341.1 IPS |
|
|
Image Super-Resolution (I8)
|
99% |
6098
217.8 IPS |
|
|
Text Classification (F32)
|
100% |
1404
2.02 KIPS |
|
|
Text Classification (F16)
|
100% |
1292
1.86 KIPS |
|
|
Text Classification (I8)
|
98% |
849
1.22 KIPS |
|
|
Machine Translation (F32)
|
100% |
2497
46.0 IPS |
|
|
Machine Translation (F16)
|
100% |
2453
45.1 IPS |
|
|
Machine Translation (I8)
|
70% |
1162
21.4 IPS |
