Win element M600
Geekbench AI Score
1791
Single Precision Score
1789
Half Precision Score
979
Quantized Score
Geekbench AI 1.3.0 for Linux AVX2
Result Information
| User | ntgreatx |
| Upload Date | May 06 2025 07:44 PM |
| Views | 8 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | AMD Ryzen 9 6900HX |
| System Information | |
|---|---|
| Operating System | Ubuntu 22.04.5 LTS |
| Model | Win element M600 |
| Motherboard | Win element M600 |
| CPU Information | |
|---|---|
| Name | AMD Ryzen 9 6900HX |
| Topology | 1 Processor, 8 Cores, 16 Threads |
| Identifier | AuthenticAMD Family 25 Model 68 Stepping 1 |
| Base Frequency | 4.93 GHz |
| Cluster 1 | 0 Cores |
| Memory Information | |
|---|---|
| Size | 62.04 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
1264
235.1 IPS |
|
|
Image Classification (HP)
|
100% |
1220
226.9 IPS |
|
|
Image Classification (Q)
|
99% |
599
111.8 IPS |
|
|
Image Segmentation (SP)
|
100% |
1691
27.4 IPS |
|
|
Image Segmentation (HP)
|
100% |
1716
27.8 IPS |
|
|
Image Segmentation (Q)
|
98% |
766
12.4 IPS |
|
|
Pose Estimation (SP)
|
100% |
2297
2.68 IPS |
|
|
Pose Estimation (HP)
|
100% |
2286
2.67 IPS |
|
|
Pose Estimation (Q)
|
96% |
2030
2.38 IPS |
|
|
Object Detection (SP)
|
100% |
1282
101.7 IPS |
|
|
Object Detection (HP)
|
100% |
1258
99.8 IPS |
|
|
Object Detection (Q)
|
85% |
589
47.4 IPS |
|
|
Face Detection (SP)
|
100% |
2236
26.6 IPS |
|
|
Face Detection (HP)
|
100% |
2285
27.2 IPS |
|
|
Face Detection (Q)
|
97% |
1482
17.7 IPS |
|
|
Depth Estimation (SP)
|
100% |
2161
16.7 IPS |
|
|
Depth Estimation (HP)
|
99% |
2172
16.7 IPS |
|
|
Depth Estimation (Q)
|
63% |
1370
12.8 IPS |
|
|
Style Transfer (SP)
|
100% |
2736
3.52 IPS |
|
|
Style Transfer (HP)
|
100% |
2762
3.55 IPS |
|
|
Style Transfer (Q)
|
98% |
3917
5.05 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
1445
53.3 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
1476
54.5 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
989
36.7 IPS |
|
|
Text Classification (SP)
|
100% |
1270
1.70 KIPS |
|
|
Text Classification (HP)
|
100% |
1247
1.66 KIPS |
|
|
Text Classification (Q)
|
92% |
406
545.3 IPS |
|
|
Machine Translation (SP)
|
100% |
2236
38.5 IPS |
|
|
Machine Translation (HP)
|
100% |
2214
38.1 IPS |
|
|
Machine Translation (Q)
|
58% |
464
10.9 IPS |
