Valve Jupiter
Geekbench AI Score
887
Single Precision Score
889
Half Precision Score
631
Quantized Score
Geekbench AI 1.2.0 for Linux AVX2
Result Information
| User | Joshua179 |
| Upload Date | February 14 2025 11:33 AM |
| Views | 5 |
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 | 3.50 GHz |
| Cluster 1 | 0 Cores |
| Memory Information | |
|---|---|
| Size | 13.48 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
512
95.2 IPS |
|
|
Image Classification (HP)
|
100% |
511
95.1 IPS |
|
|
Image Classification (Q)
|
99% |
339
63.2 IPS |
|
|
Image Segmentation (SP)
|
100% |
806
13.1 IPS |
|
|
Image Segmentation (HP)
|
100% |
794
12.9 IPS |
|
|
Image Segmentation (Q)
|
98% |
477
7.76 IPS |
|
|
Pose Estimation (SP)
|
100% |
1020
1.19 IPS |
|
|
Pose Estimation (HP)
|
100% |
1018
1.19 IPS |
|
|
Pose Estimation (Q)
|
96% |
1014
1.19 IPS |
|
|
Object Detection (SP)
|
100% |
604
47.9 IPS |
|
|
Object Detection (HP)
|
100% |
601
47.7 IPS |
|
|
Object Detection (Q)
|
85% |
443
35.7 IPS |
|
|
Face Detection (SP)
|
100% |
1154
13.7 IPS |
|
|
Face Detection (HP)
|
100% |
1166
13.9 IPS |
|
|
Face Detection (Q)
|
97% |
1018
12.1 IPS |
|
|
Depth Estimation (SP)
|
100% |
1083
8.34 IPS |
|
|
Depth Estimation (HP)
|
99% |
1080
8.32 IPS |
|
|
Depth Estimation (Q)
|
63% |
832
7.80 IPS |
|
|
Style Transfer (SP)
|
100% |
1551
1.99 IPS |
|
|
Style Transfer (HP)
|
100% |
1554
2.00 IPS |
|
|
Style Transfer (Q)
|
98% |
2130
2.75 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
588
21.7 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
585
21.6 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
594
22.0 IPS |
|
|
Text Classification (SP)
|
100% |
963
1.29 KIPS |
|
|
Text Classification (HP)
|
100% |
973
1.30 KIPS |
|
|
Text Classification (Q)
|
92% |
400
537.7 IPS |
|
|
Machine Translation (SP)
|
100% |
1082
18.6 IPS |
|
|
Machine Translation (HP)
|
100% |
1127
19.4 IPS |
|
|
Machine Translation (Q)
|
58% |
323
7.59 IPS |
