Tianbei GEM12
Geekbench AI Score
4980
Single Precision Score
5136
Half Precision Score
15642
Quantized Score
Geekbench AI 1.3.0 for Windows AVX2
Result Information
| User | neph |
| Upload Date | May 31 2025 05:33 PM |
| Views | 4 |
System Information
| AI Information | |
|---|---|
| Framework | OpenVINO |
| Backend | CPU |
| Device | AMD Ryzen 7 PRO 8845HS w/ Radeon 780M Graphics |
| System Information | |
|---|---|
| Operating System | Microsoft Windows 11 Professionnel (64-bit) |
| Model | Tianbei GEM12 |
| Motherboard | Tianbei GEM12 |
| Power Plan | Utilisation normale |
| CPU Information | |
|---|---|
| Name | AMD Ryzen 7 PRO 8845HS w/ Radeon 780M Graphics |
| Topology | 1 Processor, 8 Cores, 16 Threads |
| Identifier | AuthenticAMD Family 25 Model 117 Stepping 2 |
| Base Frequency | 3.80 GHz |
| Cluster 1 | 8 Cores |
| Memory Information | |
|---|---|
| Size | 32.00 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
3283
610.5 IPS |
|
|
Image Classification (HP)
|
100% |
3439
639.6 IPS |
|
|
Image Classification (Q)
|
100% |
10822
2.01 KIPS |
|
|
Image Segmentation (SP)
|
100% |
3302
53.5 IPS |
|
|
Image Segmentation (HP)
|
100% |
3773
61.2 IPS |
|
|
Image Segmentation (Q)
|
99% |
10514
170.4 IPS |
|
|
Pose Estimation (SP)
|
100% |
7244
8.45 IPS |
|
|
Pose Estimation (HP)
|
100% |
7246
8.45 IPS |
|
|
Pose Estimation (Q)
|
98% |
29961
35.1 IPS |
|
|
Object Detection (SP)
|
100% |
2669
211.7 IPS |
|
|
Object Detection (HP)
|
100% |
2716
215.4 IPS |
|
|
Object Detection (Q)
|
88% |
10529
844.0 IPS |
|
|
Face Detection (SP)
|
100% |
5387
64.0 IPS |
|
|
Face Detection (HP)
|
100% |
5323
63.2 IPS |
|
|
Face Detection (Q)
|
100% |
24684
293.3 IPS |
|
|
Depth Estimation (SP)
|
100% |
8606
66.3 IPS |
|
|
Depth Estimation (HP)
|
99% |
8285
63.8 IPS |
|
|
Depth Estimation (Q)
|
88% |
22604
175.9 IPS |
|
|
Style Transfer (SP)
|
100% |
19607
25.2 IPS |
|
|
Style Transfer (HP)
|
100% |
19589
25.2 IPS |
|
|
Style Transfer (Q)
|
98% |
80543
103.9 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
3599
132.9 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
3893
143.7 IPS |
|
|
Image Super-Resolution (Q)
|
99% |
15768
584.0 IPS |
|
|
Text Classification (SP)
|
100% |
3868
5.16 KIPS |
|
|
Text Classification (HP)
|
100% |
3920
5.23 KIPS |
|
|
Text Classification (Q)
|
92% |
5623
7.55 KIPS |
|
|
Machine Translation (SP)
|
100% |
3544
61.1 IPS |
|
|
Machine Translation (HP)
|
100% |
3797
65.4 IPS |
|
|
Machine Translation (Q)
|
100% |
6133
105.6 IPS |
