LENOVO F0AN
Geekbench ML Score
884
ONNX DirectML Inference Score
Geekbench ML 0.6.0 for Windows AVX2
Result Information
| Upload Date | October 02 2024 03:39 AM |
| Views | 1 |
System Information
| System Information | |
|---|---|
| Operating System | Microsoft Windows 11 Home (64-bit) |
| Model | LENOVO F0AN |
| Motherboard | LENOVO INVALID |
| Power Plan | Balanced |
| CPU Information | |
|---|---|
| Name | Intel Core i7-4558U |
| Topology | 1 Processor, 2 Cores, 4 Threads |
| Identifier | GenuineIntel Family 6 Model 69 Stepping 1 |
| Base Frequency | 2.80 GHz |
| Cluster 1 | 2 Cores |
| L1 Instruction Cache | 32.0 KB x 2 |
| L1 Data Cache | 32.0 KB x 2 |
| L2 Cache | 256 KB x 2 |
| L3 Cache | 4.00 MB x 1 |
| Memory Information | |
|---|---|
| Size | 8.00 GB |
| Inference Information | |
|---|---|
| Framework | ONNX |
| Backend | DirectML |
| Device | NVIDIA GeForce 840A |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
368
69.0 IPS |
|
|
Image Classification (F16)
|
100% |
364
68.1 IPS |
|
|
Image Classification (I8)
|
100% |
310
58.0 IPS |
|
|
Image Segmentation (F32)
|
100% |
418
6.98 IPS |
|
|
Image Segmentation (F16)
|
100% |
411
6.86 IPS |
|
|
Image Segmentation (I8)
|
98% |
354
5.92 IPS |
|
|
Pose Estimation (F32)
|
100% |
3950
4.78 IPS |
|
|
Pose Estimation (F16)
|
100% |
3937
4.77 IPS |
|
|
Pose Estimation (I8)
|
100% |
3184
3.86 IPS |
|
|
Object Detection (F32)
|
100% |
332
24.8 IPS |
|
|
Object Detection (F16)
|
100% |
418
31.2 IPS |
|
|
Object Detection (I8)
|
60% |
294
21.9 IPS |
|
|
Face Detection (F32)
|
100% |
691
8.21 IPS |
|
|
Face Detection (F16)
|
100% |
686
8.16 IPS |
|
|
Face Detection (I8)
|
89% |
578
6.87 IPS |
|
|
Depth Estimation (F32)
|
100% |
1866
14.5 IPS |
|
|
Depth Estimation (F16)
|
100% |
1857
14.4 IPS |
|
|
Depth Estimation (I8)
|
95% |
1541
12.0 IPS |
|
|
Style Transfer (F32)
|
100% |
6306
8.29 IPS |
|
|
Style Transfer (F16)
|
100% |
6316
8.31 IPS |
|
|
Style Transfer (I8)
|
98% |
5151
6.78 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
1746
62.4 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
1682
60.1 IPS |
|
|
Image Super-Resolution (I8)
|
99% |
1157
41.3 IPS |
|
|
Text Classification (F32)
|
100% |
489
702.1 IPS |
|
|
Text Classification (F16)
|
100% |
487
699.7 IPS |
|
|
Text Classification (I8)
|
98% |
285
409.3 IPS |
|
|
Machine Translation (F32)
|
100% |
490
9.02 IPS |
|
|
Machine Translation (F16)
|
100% |
484
8.90 IPS |
|
|
Machine Translation (I8)
|
68% |
299
5.50 IPS |
