Generic
Geekbench AI Score
1294
Single Precision Score
677
Half Precision Score
1594
Quantized Score
Geekbench AI 1.2.0 for Windows AVX2
Result Information
| User | lcastell |
| Upload Date | December 31 2024 12:04 AM |
| Views | 2 |
System Information
| AI Information | |
|---|---|
| Framework | ONNX |
| Backend | CPU |
| Device | AMD Ryzen 7 2700X |
| System Information | |
|---|---|
| Operating System | Microsoft Windows 11 Pro (64-bit) |
| Model | Generic |
| Motherboard | ASRock B450M Pro4 |
| Power Plan | High performance |
| CPU Information | |
|---|---|
| Name | AMD Ryzen 7 2700X |
| Topology | 1 Processor, 8 Cores, 16 Threads |
| Identifier | AuthenticAMD Family 23 Model 8 Stepping 2 |
| Base Frequency | 3.70 GHz |
| Cluster 1 | 8 Cores |
| Memory Information | |
|---|---|
| Size | 48.00 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
946
176.0 IPS |
|
|
Image Classification (HP)
|
100% |
266
49.4 IPS |
|
|
Image Classification (Q)
|
96% |
1301
242.9 IPS |
|
|
Image Segmentation (SP)
|
100% |
521
8.44 IPS |
|
|
Image Segmentation (HP)
|
100% |
352
5.70 IPS |
|
|
Image Segmentation (Q)
|
97% |
1114
18.1 IPS |
|
|
Pose Estimation (SP)
|
100% |
2160
2.52 IPS |
|
|
Pose Estimation (HP)
|
100% |
1812
2.11 IPS |
|
|
Pose Estimation (Q)
|
86% |
2608
3.08 IPS |
|
|
Object Detection (SP)
|
100% |
936
74.3 IPS |
|
|
Object Detection (HP)
|
100% |
324
25.7 IPS |
|
|
Object Detection (Q)
|
58% |
858
93.8 IPS |
|
|
Face Detection (SP)
|
100% |
1931
22.9 IPS |
|
|
Face Detection (HP)
|
100% |
738
8.77 IPS |
|
|
Face Detection (Q)
|
96% |
3000
35.8 IPS |
|
|
Depth Estimation (SP)
|
100% |
2705
20.8 IPS |
|
|
Depth Estimation (HP)
|
99% |
1045
8.05 IPS |
|
|
Depth Estimation (Q)
|
78% |
3056
24.4 IPS |
|
|
Style Transfer (SP)
|
100% |
5480
7.04 IPS |
|
|
Style Transfer (HP)
|
100% |
4658
5.99 IPS |
|
|
Style Transfer (Q)
|
87% |
5590
7.28 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
858
31.7 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
839
31.0 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
1045
38.7 IPS |
|
|
Text Classification (SP)
|
100% |
645
861.3 IPS |
|
|
Text Classification (HP)
|
100% |
323
431.4 IPS |
|
|
Text Classification (Q)
|
97% |
572
765.9 IPS |
|
|
Machine Translation (SP)
|
100% |
836
14.4 IPS |
|
|
Machine Translation (HP)
|
100% |
378
6.52 IPS |
|
|
Machine Translation (Q)
|
68% |
1070
20.7 IPS |
