TOPC PHX ITX
Geekbench AI Score
3395
Single Precision Score
1690
Half Precision Score
5151
Quantized Score
Geekbench AI 1.1.0 for Windows AVX2
Result Information
| Upload Date | November 21 2024 05:44 AM |
| Views | 2 |
System Information
| AI Information | |
|---|---|
| Framework | ONNX |
| Backend | CPU |
| Device | AMD Eng Sample: 100-000000954-50_Y |
| System Information | |
|---|---|
| Operating System | Microsoft Windows 11 Pro (64-bit) |
| Model | TOPC PHX ITX |
| Motherboard | TOPC PHX |
| CPU Information | |
|---|---|
| Name | AMD Eng Sample: 100-000000954-50_Y |
| Topology | 1 Processor, 8 Cores, 16 Threads |
| Identifier | AuthenticAMD Family 25 Model 116 Stepping 0 |
| Base Frequency | 3.70 GHz |
| Cluster 1 | 8 Cores |
| Memory Information | |
|---|---|
| Size | 64.00 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
1961
364.6 IPS |
|
|
Image Classification (HP)
|
100% |
591
109.9 IPS |
|
|
Image Classification (Q)
|
99% |
5126
956.2 IPS |
|
|
Image Segmentation (SP)
|
100% |
1255
20.3 IPS |
|
|
Image Segmentation (HP)
|
100% |
826
13.4 IPS |
|
|
Image Segmentation (Q)
|
98% |
3637
59.1 IPS |
|
|
Pose Estimation (SP)
|
100% |
6263
7.31 IPS |
|
|
Pose Estimation (HP)
|
100% |
5493
6.41 IPS |
|
|
Pose Estimation (Q)
|
95% |
25962
30.4 IPS |
|
|
Object Detection (SP)
|
100% |
2474
196.2 IPS |
|
|
Object Detection (HP)
|
100% |
775
61.5 IPS |
|
|
Object Detection (Q)
|
88% |
2222
178.1 IPS |
|
|
Face Detection (SP)
|
100% |
3231
38.4 IPS |
|
|
Face Detection (HP)
|
100% |
1788
21.2 IPS |
|
|
Face Detection (Q)
|
97% |
5334
63.6 IPS |
|
|
Depth Estimation (SP)
|
100% |
7821
60.3 IPS |
|
|
Depth Estimation (HP)
|
99% |
2671
20.6 IPS |
|
|
Depth Estimation (Q)
|
77% |
5263
42.1 IPS |
|
|
Style Transfer (SP)
|
100% |
16397
21.1 IPS |
|
|
Style Transfer (HP)
|
100% |
14309
18.4 IPS |
|
|
Style Transfer (Q)
|
98% |
26323
33.9 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
2699
99.7 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
2395
88.4 IPS |
|
|
Image Super-Resolution (Q)
|
99% |
3672
136.0 IPS |
|
|
Text Classification (SP)
|
100% |
2123
2.83 KIPS |
|
|
Text Classification (HP)
|
100% |
797
1.06 KIPS |
|
|
Text Classification (Q)
|
97% |
1818
2.44 KIPS |
|
|
Machine Translation (SP)
|
100% |
2251
38.8 IPS |
|
|
Machine Translation (HP)
|
100% |
702
12.1 IPS |
|
|
Machine Translation (Q)
|
60% |
2481
55.3 IPS |
