Valve Jupiter
Geekbench AI Score
1567
Single Precision Score
1563
Half Precision Score
2239
Quantized Score
Geekbench AI 1.2.0 for Linux AVX2
Result Information
| User | CoreRemnant |
| Upload Date | January 09 2025 04:56 PM |
| Views | 4 |
System Information
| AI Information | |
|---|---|
| Framework | OpenVINO |
| Backend | CPU |
| Device | AMD Custom APU 0405 AmdCcxVhFf3PeiInit 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 | 14.46 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
1027
191.0 IPS |
|
|
Image Classification (HP)
|
100% |
997
185.4 IPS |
|
|
Image Classification (Q)
|
100% |
1446
268.9 IPS |
|
|
Image Segmentation (SP)
|
100% |
462
7.48 IPS |
|
|
Image Segmentation (HP)
|
100% |
489
7.92 IPS |
|
|
Image Segmentation (Q)
|
99% |
1023
16.6 IPS |
|
|
Pose Estimation (SP)
|
100% |
2113
2.47 IPS |
|
|
Pose Estimation (HP)
|
100% |
2062
2.41 IPS |
|
|
Pose Estimation (Q)
|
94% |
2972
3.49 IPS |
|
|
Object Detection (SP)
|
100% |
947
75.1 IPS |
|
|
Object Detection (HP)
|
100% |
928
73.6 IPS |
|
|
Object Detection (Q)
|
87% |
1454
116.6 IPS |
|
|
Face Detection (SP)
|
100% |
2238
26.6 IPS |
|
|
Face Detection (HP)
|
100% |
2264
26.9 IPS |
|
|
Face Detection (Q)
|
97% |
4269
50.9 IPS |
|
|
Depth Estimation (SP)
|
100% |
2742
21.1 IPS |
|
|
Depth Estimation (HP)
|
99% |
2704
20.8 IPS |
|
|
Depth Estimation (Q)
|
81% |
3763
29.7 IPS |
|
|
Style Transfer (SP)
|
100% |
6058
7.79 IPS |
|
|
Style Transfer (HP)
|
100% |
6090
7.83 IPS |
|
|
Style Transfer (Q)
|
98% |
8612
11.1 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
1220
45.0 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
1201
44.3 IPS |
|
|
Image Super-Resolution (Q)
|
98% |
1816
67.3 IPS |
|
|
Text Classification (SP)
|
100% |
1286
1.72 KIPS |
|
|
Text Classification (HP)
|
100% |
1266
1.69 KIPS |
|
|
Text Classification (Q)
|
91% |
1201
1.61 KIPS |
|
|
Machine Translation (SP)
|
100% |
1622
27.9 IPS |
|
|
Machine Translation (HP)
|
100% |
1655
28.5 IPS |
|
|
Machine Translation (Q)
|
100% |
1647
28.4 IPS |
