Suma W550-H30
Geekbench AI Score
91
Single Precision Score
91
Half Precision Score
68
Quantized Score
Geekbench AI 1.2.0 for Linux x86 (64-bit)
Result Information
| Upload Date | January 06 2025 03:45 AM |
| Views | 17 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | Hygon C86 3350 8-core Processor |
| System Information | |
|---|---|
| Operating System | Ubuntu 22.04.5 LTS |
| Model | Suma W550-H30 |
| Motherboard | Suma 42DA8 |
| CPU Information | |
|---|---|
| Name | Hygon C86 3350 8-core Processor |
| Topology | 2 Processors, 16 Cores, 32 Threads |
| Identifier | HygonGenuine Family 24 Model 2 Stepping 2 |
| Base Frequency | 3.00 GHz |
| Cluster 1 | 0 Cores |
| Memory Information | |
|---|---|
| Size | 125.80 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
53
9.95 IPS |
|
|
Image Classification (HP)
|
100% |
54
9.95 IPS |
|
|
Image Classification (Q)
|
97% |
43
8.09 IPS |
|
|
Image Segmentation (SP)
|
100% |
73
1.18 IPS |
|
|
Image Segmentation (HP)
|
100% |
73
1.18 IPS |
|
|
Image Segmentation (Q)
|
98% |
56
0.91 IPS |
|
|
Pose Estimation (SP)
|
100% |
90
0.10 IPS |
|
|
Pose Estimation (HP)
|
100% |
90
0.10 IPS |
|
|
Pose Estimation (Q)
|
96% |
76
0.09 IPS |
|
|
Object Detection (SP)
|
100% |
53
4.19 IPS |
|
|
Object Detection (HP)
|
100% |
53
4.17 IPS |
|
|
Object Detection (Q)
|
87% |
43
3.41 IPS |
|
|
Face Detection (SP)
|
100% |
168
1.99 IPS |
|
|
Face Detection (HP)
|
100% |
167
1.99 IPS |
|
|
Face Detection (Q)
|
97% |
129
1.54 IPS |
|
|
Depth Estimation (SP)
|
100% |
125
0.96 IPS |
|
|
Depth Estimation (HP)
|
99% |
125
0.96 IPS |
|
|
Depth Estimation (Q)
|
64% |
86
0.79 IPS |
|
|
Style Transfer (SP)
|
100% |
266
0.34 IPS |
|
|
Style Transfer (HP)
|
100% |
267
0.34 IPS |
|
|
Style Transfer (Q)
|
98% |
228
0.29 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
56
2.07 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
56
2.06 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
47
1.73 IPS |
|
|
Text Classification (SP)
|
100% |
65
86.9 IPS |
|
|
Text Classification (HP)
|
100% |
65
86.7 IPS |
|
|
Text Classification (Q)
|
91% |
46
62.0 IPS |
|
|
Machine Translation (SP)
|
100% |
110
1.89 IPS |
|
|
Machine Translation (HP)
|
100% |
108
1.86 IPS |
|
|
Machine Translation (Q)
|
58% |
52
1.25 IPS |
