AZW SER9
Geekbench AI Score
2111
Single Precision Score
2100
Half Precision Score
1799
Quantized Score
Geekbench AI 1.7.0 for Linux AVX2
Result Information
| User | Light_Foot |
| Upload Date | February 27 2026 08:29 PM |
| Views | 12 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | AMD Ryzen AI 9 HX 370 |
| System Information | |
|---|---|
| Operating System | Fedora Linux 43 (Workstation Edition) |
| Model | AZW SER9 |
| Motherboard | AZW SER9 |
| CPU Information | |
|---|---|
| Name | AMD Ryzen AI 9 HX 370 |
| Topology | 1 Processor, 12 Cores, 24 Threads |
| Identifier | AuthenticAMD Family 26 Model 36 Stepping 0 |
| Base Frequency | 5.23 GHz |
| Cluster 1 | 0 Cores |
| Memory Information | |
|---|---|
| Size | 30.42 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
1176
218.7 IPS |
|
|
Image Classification (HP)
|
100% |
1159
215.5 IPS |
|
|
Image Classification (Q)
|
99% |
1238
230.8 IPS |
|
|
Image Segmentation (SP)
|
100% |
2121
34.4 IPS |
|
|
Image Segmentation (HP)
|
100% |
2147
34.8 IPS |
|
|
Image Segmentation (Q)
|
98% |
1252
20.3 IPS |
|
|
Pose Estimation (SP)
|
100% |
3028
3.53 IPS |
|
|
Pose Estimation (HP)
|
100% |
2991
3.49 IPS |
|
|
Pose Estimation (Q)
|
96% |
3816
4.47 IPS |
|
|
Object Detection (SP)
|
100% |
1268
100.6 IPS |
|
|
Object Detection (HP)
|
100% |
1307
103.7 IPS |
|
|
Object Detection (Q)
|
85% |
1277
102.8 IPS |
|
|
Face Detection (SP)
|
100% |
2777
33.0 IPS |
|
|
Face Detection (HP)
|
100% |
2746
32.6 IPS |
|
|
Face Detection (Q)
|
97% |
2726
32.5 IPS |
|
|
Depth Estimation (SP)
|
100% |
2528
19.5 IPS |
|
|
Depth Estimation (HP)
|
99% |
2514
19.4 IPS |
|
|
Depth Estimation (Q)
|
63% |
2321
21.8 IPS |
|
|
Style Transfer (SP)
|
100% |
4075
5.24 IPS |
|
|
Style Transfer (HP)
|
100% |
3964
5.10 IPS |
|
|
Style Transfer (Q)
|
98% |
6719
8.66 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
1363
50.3 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
1376
50.8 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
1870
69.3 IPS |
|
|
Text Classification (SP)
|
100% |
1528
2.04 KIPS |
|
|
Text Classification (HP)
|
100% |
1521
2.03 KIPS |
|
|
Text Classification (Q)
|
92% |
800
1.07 KIPS |
|
|
Machine Translation (SP)
|
100% |
3092
53.3 IPS |
|
|
Machine Translation (HP)
|
100% |
3006
51.8 IPS |
|
|
Machine Translation (Q)
|
58% |
742
17.4 IPS |
