ASUS System Product Name
Geekbench AI Score
33563
Single Precision Score
44385
Half Precision Score
25455
Quantized Score
Geekbench AI 1.1.0 Corporate for Windows AVX2
Result Information
| User | SoulRipper |
| Upload Date | September 25 2024 06:12 PM |
| Views | 4 |
System Information
| AI Information | |
|---|---|
| Framework | ONNX |
| Backend | DirectML |
| Device | NVIDIA GeForce RTX 4090 |
| System Information | |
|---|---|
| Operating System | Microsoft Windows 10 Enterprise LTSC (64-bit) |
| Model | ASUS System Product Name |
| Motherboard | ASUSTeK COMPUTER INC. ROG CROSSHAIR VII HERO |
| Power Plan | High performance |
| CPU Information | |
|---|---|
| Name | AMD Ryzen 9 5950X |
| Topology | 1 Processor, 16 Cores, 32 Threads |
| Identifier | AuthenticAMD Family 25 Model 33 Stepping 0 |
| Base Frequency | 3.40 GHz |
| Cluster 1 | 16 Cores |
| Memory Information | |
|---|---|
| Size | 64.00 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
12246
2.28 KIPS |
|
|
Image Classification (HP)
|
99% |
15690
2.93 KIPS |
|
|
Image Classification (Q)
|
100% |
10451
1.94 KIPS |
|
|
Image Segmentation (SP)
|
100% |
18102
293.4 IPS |
|
|
Image Segmentation (HP)
|
100% |
21083
341.8 IPS |
|
|
Image Segmentation (Q)
|
98% |
16912
275.0 IPS |
|
|
Pose Estimation (SP)
|
100% |
304305
355.1 IPS |
|
|
Pose Estimation (HP)
|
100% |
511239
596.5 IPS |
|
|
Pose Estimation (Q)
|
97% |
265585
311.0 IPS |
|
|
Object Detection (SP)
|
100% |
16168
1.28 KIPS |
|
|
Object Detection (HP)
|
100% |
20017
1.59 KIPS |
|
|
Object Detection (Q)
|
89% |
13222
1.06 KIPS |
|
|
Face Detection (SP)
|
100% |
41819
496.9 IPS |
|
|
Face Detection (HP)
|
100% |
49164
584.2 IPS |
|
|
Face Detection (Q)
|
97% |
34543
411.9 IPS |
|
|
Depth Estimation (SP)
|
100% |
87518
674.3 IPS |
|
|
Depth Estimation (HP)
|
99% |
144251
1.11 KIPS |
|
|
Depth Estimation (Q)
|
76% |
63902
514.0 IPS |
|
|
Style Transfer (SP)
|
100% |
542827
697.8 IPS |
|
|
Style Transfer (HP)
|
100% |
980808
1.26 KIPS |
|
|
Style Transfer (Q)
|
98% |
466373
601.4 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
56389
2.08 KIPS |
|
|
Image Super-Resolution (HP)
|
100% |
73305
2.71 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
42147
1.56 KIPS |
|
|
Text Classification (SP)
|
100% |
3355
4.48 KIPS |
|
|
Text Classification (HP)
|
99% |
3991
5.33 KIPS |
|
|
Text Classification (Q)
|
97% |
2133
2.86 KIPS |
|
|
Machine Translation (SP)
|
100% |
4425
76.2 IPS |
|
|
Machine Translation (HP)
|
100% |
4308
74.2 IPS |
|
|
Machine Translation (Q)
|
60% |
1989
44.4 IPS |
