Generic
Geekbench ML Score
7160
ONNX DirectML Inference Score
Geekbench ML 0.6.0 for Windows AVX2
Result Information
| User | monopuerco |
| Upload Date | August 15 2024 05:50 PM |
| Views | 1 |
System Information
| System Information | |
|---|---|
| Operating System | Microsoft Windows 11 Home (64-bit) |
| Model | Generic |
| Motherboard | ASRock Z370 Killer SLI/ac |
| Power Plan | Balanced |
| CPU Information | |
|---|---|
| Name | Intel Core i5-8600K |
| Topology | 1 Processor, 6 Cores |
| Identifier | GenuineIntel Family 6 Model 158 Stepping 10 |
| Base Frequency | 3.60 GHz |
| Cluster 1 | 6 Cores |
| L1 Instruction Cache | 32.0 KB x 3 |
| L1 Data Cache | 32.0 KB x 3 |
| L2 Cache | 256 KB x 3 |
| L3 Cache | 9.00 MB x 1 |
| Memory Information | |
|---|---|
| Size | 32.00 GB |
| Inference Information | |
|---|---|
| Framework | ONNX |
| Backend | DirectML |
| Device | NVIDIA GeForce GTX 1070 Ti |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
2332
436.3 IPS |
|
|
Image Classification (F16)
|
100% |
2299
430.1 IPS |
|
|
Image Classification (I8)
|
100% |
1967
368.1 IPS |
|
|
Image Segmentation (F32)
|
100% |
4617
77.1 IPS |
|
|
Image Segmentation (F16)
|
100% |
4847
81.0 IPS |
|
|
Image Segmentation (I8)
|
98% |
3962
66.2 IPS |
|
|
Pose Estimation (F32)
|
100% |
59779
72.4 IPS |
|
|
Pose Estimation (F16)
|
100% |
59814
72.4 IPS |
|
|
Pose Estimation (I8)
|
100% |
46210
56.0 IPS |
|
|
Object Detection (F32)
|
100% |
2193
163.7 IPS |
|
|
Object Detection (F16)
|
100% |
1541
115.0 IPS |
|
|
Object Detection (I8)
|
61% |
2044
152.6 IPS |
|
|
Face Detection (F32)
|
100% |
5692
67.7 IPS |
|
|
Face Detection (F16)
|
100% |
5890
70.0 IPS |
|
|
Face Detection (I8)
|
89% |
4680
55.6 IPS |
|
|
Depth Estimation (F32)
|
100% |
18926
146.8 IPS |
|
|
Depth Estimation (F16)
|
100% |
18883
146.4 IPS |
|
|
Depth Estimation (I8)
|
95% |
15454
119.8 IPS |
|
|
Style Transfer (F32)
|
100% |
107524
141.4 IPS |
|
|
Style Transfer (F16)
|
100% |
108330
142.5 IPS |
|
|
Style Transfer (I8)
|
98% |
79106
104.1 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
18242
651.5 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
18568
663.1 IPS |
|
|
Image Super-Resolution (I8)
|
99% |
10961
391.5 IPS |
|
|
Text Classification (F32)
|
100% |
1361
1.96 KIPS |
|
|
Text Classification (F16)
|
100% |
1319
1.90 KIPS |
|
|
Text Classification (I8)
|
98% |
878
1.26 KIPS |
|
|
Machine Translation (F32)
|
100% |
2415
44.4 IPS |
|
|
Machine Translation (F16)
|
100% |
2588
47.6 IPS |
|
|
Machine Translation (I8)
|
70% |
1428
26.3 IPS |
