AZW SER
Geekbench AI Score
2776
Single Precision Score
1220
Half Precision Score
4073
Quantized Score
Geekbench AI 1.2.0 for Windows AVX2
Result Information
| User | fraludio |
| Upload Date | March 08 2025 10:09 PM |
| Views | 6 |
System Information
| AI Information | |
|---|---|
| Framework | ONNX |
| Backend | CPU |
| Device | AMD Ryzen 7 5800H |
| System Information | |
|---|---|
| Operating System | Microsoft Windows 11 Pro (64-bit) |
| Model | AZW SER |
| Motherboard | AZW SER |
| Power Plan | Alto rendimiento |
| CPU Information | |
|---|---|
| Name | AMD Ryzen 7 5800H |
| Topology | 1 Processor, 8 Cores, 16 Threads |
| Identifier | AuthenticAMD Family 25 Model 80 Stepping 0 |
| Base Frequency | 3.20 GHz |
| Cluster 1 | 8 Cores |
| Memory Information | |
|---|---|
| Size | 32.00 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
2476
460.4 IPS |
|
|
Image Classification (HP)
|
100% |
449
83.4 IPS |
|
|
Image Classification (Q)
|
96% |
4273
798.0 IPS |
|
|
Image Segmentation (SP)
|
100% |
1168
18.9 IPS |
|
|
Image Segmentation (HP)
|
100% |
661
10.7 IPS |
|
|
Image Segmentation (Q)
|
97% |
2361
38.4 IPS |
|
|
Pose Estimation (SP)
|
100% |
4754
5.55 IPS |
|
|
Pose Estimation (HP)
|
100% |
3593
4.19 IPS |
|
|
Pose Estimation (Q)
|
86% |
9604
11.4 IPS |
|
|
Object Detection (SP)
|
100% |
2276
180.5 IPS |
|
|
Object Detection (HP)
|
100% |
597
47.3 IPS |
|
|
Object Detection (Q)
|
58% |
2724
297.7 IPS |
|
|
Face Detection (SP)
|
100% |
3098
36.8 IPS |
|
|
Face Detection (HP)
|
100% |
1159
13.8 IPS |
|
|
Face Detection (Q)
|
96% |
6594
78.7 IPS |
|
|
Depth Estimation (SP)
|
100% |
6372
49.1 IPS |
|
|
Depth Estimation (HP)
|
99% |
1829
14.1 IPS |
|
|
Depth Estimation (Q)
|
78% |
9061
72.3 IPS |
|
|
Style Transfer (SP)
|
100% |
11052
14.2 IPS |
|
|
Style Transfer (HP)
|
100% |
9296
12.0 IPS |
|
|
Style Transfer (Q)
|
87% |
12771
16.6 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
1880
69.4 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
1610
59.4 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
2351
87.1 IPS |
|
|
Text Classification (SP)
|
100% |
1261
1.68 KIPS |
|
|
Text Classification (HP)
|
100% |
645
861.0 IPS |
|
|
Text Classification (Q)
|
97% |
1355
1.81 KIPS |
|
|
Machine Translation (SP)
|
100% |
1682
29.0 IPS |
|
|
Machine Translation (HP)
|
100% |
562
9.68 IPS |
|
|
Machine Translation (Q)
|
68% |
1963
37.9 IPS |
