Valve Jupiter
Geekbench AI Score
936
Single Precision Score
937
Half Precision Score
659
Quantized Score
Geekbench AI 1.2.0 for Linux AVX2
Result Information
| Upload Date | December 03 2024 10:20 PM |
| Views | 4 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | AMD Custom APU 04053PeiInit Entry |
| System Information | |
|---|---|
| Operating System | SteamOS |
| Model | Valve Jupiter |
| Motherboard | Valve Jupiter |
| CPU Information | |
|---|---|
| Name | Intel Pentium II/III |
| Topology | 1 Processor, 4 Cores, 8 Threads |
| Identifier | AuthenticAMD Family 23 Model 144 Stepping 2 |
| Base Frequency | 4.01 GHz |
| Cluster 1 | 0 Cores |
| Memory Information | |
|---|---|
| Size | 14.46 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
539
100.3 IPS |
|
|
Image Classification (HP)
|
100% |
536
99.7 IPS |
|
|
Image Classification (Q)
|
99% |
342
63.8 IPS |
|
|
Image Segmentation (SP)
|
100% |
830
13.4 IPS |
|
|
Image Segmentation (HP)
|
100% |
822
13.3 IPS |
|
|
Image Segmentation (Q)
|
98% |
500
8.13 IPS |
|
|
Pose Estimation (SP)
|
100% |
1095
1.28 IPS |
|
|
Pose Estimation (HP)
|
100% |
1089
1.27 IPS |
|
|
Pose Estimation (Q)
|
96% |
1067
1.25 IPS |
|
|
Object Detection (SP)
|
100% |
637
50.5 IPS |
|
|
Object Detection (HP)
|
100% |
635
50.4 IPS |
|
|
Object Detection (Q)
|
85% |
473
38.1 IPS |
|
|
Face Detection (SP)
|
100% |
1252
14.9 IPS |
|
|
Face Detection (HP)
|
100% |
1247
14.8 IPS |
|
|
Face Detection (Q)
|
97% |
1093
13.0 IPS |
|
|
Depth Estimation (SP)
|
100% |
1158
8.92 IPS |
|
|
Depth Estimation (HP)
|
99% |
1152
8.87 IPS |
|
|
Depth Estimation (Q)
|
63% |
874
8.20 IPS |
|
|
Style Transfer (SP)
|
100% |
1640
2.11 IPS |
|
|
Style Transfer (HP)
|
100% |
1642
2.11 IPS |
|
|
Style Transfer (Q)
|
98% |
2230
2.88 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
630
23.3 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
628
23.2 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
620
23.0 IPS |
|
|
Text Classification (SP)
|
100% |
960
1.28 KIPS |
|
|
Text Classification (HP)
|
100% |
978
1.31 KIPS |
|
|
Text Classification (Q)
|
92% |
407
546.8 IPS |
|
|
Machine Translation (SP)
|
100% |
1155
19.9 IPS |
|
|
Machine Translation (HP)
|
100% |
1186
20.4 IPS |
|
|
Machine Translation (Q)
|
58% |
335
7.88 IPS |
