Valve Jupiter
Geekbench AI Score
1600
Single Precision Score
1597
Half Precision Score
2278
Quantized Score
Geekbench AI 1.2.0 for Linux AVX2
Result Information
| User | unixwizard |
| Upload Date | February 10 2025 02:06 PM |
| Views | 10 |
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% |
1038
193.0 IPS |
|
|
Image Classification (HP)
|
100% |
1043
194.0 IPS |
|
|
Image Classification (Q)
|
100% |
1481
275.4 IPS |
|
|
Image Segmentation (SP)
|
100% |
471
7.64 IPS |
|
|
Image Segmentation (HP)
|
100% |
482
7.81 IPS |
|
|
Image Segmentation (Q)
|
99% |
995
16.2 IPS |
|
|
Pose Estimation (SP)
|
100% |
2152
2.51 IPS |
|
|
Pose Estimation (HP)
|
100% |
2103
2.45 IPS |
|
|
Pose Estimation (Q)
|
94% |
3041
3.57 IPS |
|
|
Object Detection (SP)
|
100% |
966
76.6 IPS |
|
|
Object Detection (HP)
|
100% |
957
75.9 IPS |
|
|
Object Detection (Q)
|
87% |
1488
119.3 IPS |
|
|
Face Detection (SP)
|
100% |
2240
26.6 IPS |
|
|
Face Detection (HP)
|
100% |
2285
27.2 IPS |
|
|
Face Detection (Q)
|
97% |
4383
52.3 IPS |
|
|
Depth Estimation (SP)
|
100% |
2815
21.7 IPS |
|
|
Depth Estimation (HP)
|
99% |
2764
21.3 IPS |
|
|
Depth Estimation (Q)
|
81% |
3851
30.4 IPS |
|
|
Style Transfer (SP)
|
100% |
6330
8.14 IPS |
|
|
Style Transfer (HP)
|
100% |
6179
7.94 IPS |
|
|
Style Transfer (Q)
|
98% |
8836
11.4 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
1250
46.1 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
1228
45.3 IPS |
|
|
Image Super-Resolution (Q)
|
98% |
1866
69.1 IPS |
|
|
Text Classification (SP)
|
100% |
1322
1.76 KIPS |
|
|
Text Classification (HP)
|
100% |
1327
1.77 KIPS |
|
|
Text Classification (Q)
|
91% |
1219
1.64 KIPS |
|
|
Machine Translation (SP)
|
100% |
1646
28.3 IPS |
|
|
Machine Translation (HP)
|
100% |
1685
29.0 IPS |
|
|
Machine Translation (Q)
|
100% |
1670
28.8 IPS |
