TianBei WTR PRO
Geekbench AI Score
1820
Single Precision Score
1801
Half Precision Score
1198
Quantized Score
Geekbench AI 1.2.0 for Linux AVX2
Result Information
| User | AndyMcSchopf |
| Upload Date | January 07 2025 07:48 AM |
| Views | 2 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | AMD Ryzen 7 5825U |
| System Information | |
|---|---|
| Operating System | Debian GNU/Linux 12 (bookworm) |
| Model | TianBei WTR PRO |
| Motherboard | TianBei WTR PRO |
| CPU Information | |
|---|---|
| Name | AMD Ryzen 7 5825U |
| Topology | 1 Processor, 8 Cores, 16 Threads |
| Identifier | AuthenticAMD Family 25 Model 80 Stepping 0 |
| Base Frequency | 4.55 GHz |
| Cluster 1 | 0 Cores |
| Memory Information | |
|---|---|
| Size | 62.24 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
1604
298.3 IPS |
|
|
Image Classification (HP)
|
100% |
1532
285.0 IPS |
|
|
Image Classification (Q)
|
99% |
888
165.6 IPS |
|
|
Image Segmentation (SP)
|
100% |
1760
28.5 IPS |
|
|
Image Segmentation (HP)
|
100% |
1736
28.1 IPS |
|
|
Image Segmentation (Q)
|
98% |
884
14.4 IPS |
|
|
Pose Estimation (SP)
|
100% |
1866
2.18 IPS |
|
|
Pose Estimation (HP)
|
100% |
1879
2.19 IPS |
|
|
Pose Estimation (Q)
|
96% |
2034
2.38 IPS |
|
|
Object Detection (SP)
|
100% |
1248
99.0 IPS |
|
|
Object Detection (HP)
|
100% |
1279
101.5 IPS |
|
|
Object Detection (Q)
|
85% |
767
61.7 IPS |
|
|
Face Detection (SP)
|
100% |
2111
25.1 IPS |
|
|
Face Detection (HP)
|
100% |
2111
25.1 IPS |
|
|
Face Detection (Q)
|
97% |
1954
23.3 IPS |
|
|
Depth Estimation (SP)
|
100% |
1856
14.3 IPS |
|
|
Depth Estimation (HP)
|
99% |
1848
14.2 IPS |
|
|
Depth Estimation (Q)
|
63% |
1544
14.5 IPS |
|
|
Style Transfer (SP)
|
100% |
2137
2.75 IPS |
|
|
Style Transfer (HP)
|
100% |
2145
2.76 IPS |
|
|
Style Transfer (Q)
|
98% |
3967
5.12 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
1691
62.5 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
1710
63.1 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
1219
45.2 IPS |
|
|
Text Classification (SP)
|
100% |
2003
2.67 KIPS |
|
|
Text Classification (HP)
|
100% |
1967
2.62 KIPS |
|
|
Text Classification (Q)
|
92% |
656
880.7 IPS |
|
|
Machine Translation (SP)
|
100% |
2148
37.0 IPS |
|
|
Machine Translation (HP)
|
100% |
1999
34.4 IPS |
|
|
Machine Translation (Q)
|
58% |
523
12.3 IPS |
