Generic
Geekbench AI Score
1450
Single Precision Score
749
Half Precision Score
2269
Quantized Score
Geekbench AI 1.6.0 for Windows AVX2
Result Information
| User | WheelerTowers |
| Upload Date | January 23 2026 12:36 PM |
| Views | 7 |
System Information
| AI Information | |
|---|---|
| Framework | ONNX |
| Backend | CPU |
| Device | Intel Core i3-8100 |
| System Information | |
|---|---|
| Operating System | Microsoft Windows 11 Pro (64-bit) |
| Model | Generic |
| Motherboard | ASRock B365 Pro4 |
| Power Plan | Balanced |
| CPU Information | |
|---|---|
| Name | Intel Core i3-8100 |
| Topology | 1 Processor, 4 Cores |
| Identifier | GenuineIntel Family 6 Model 158 Stepping 11 |
| Base Frequency | 3.60 GHz |
| Cluster 1 | 4 Cores |
| Memory Information | |
|---|---|
| Size | 16.00 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
1128
209.8 IPS |
|
|
Image Classification (HP)
|
100% |
280
52.0 IPS |
|
|
Image Classification (Q)
|
96% |
1750
326.8 IPS |
|
|
Image Segmentation (SP)
|
100% |
541
8.78 IPS |
|
|
Image Segmentation (HP)
|
100% |
391
6.34 IPS |
|
|
Image Segmentation (Q)
|
97% |
2116
34.4 IPS |
|
|
Pose Estimation (SP)
|
100% |
2403
2.80 IPS |
|
|
Pose Estimation (HP)
|
100% |
2102
2.45 IPS |
|
|
Pose Estimation (Q)
|
86% |
4655
5.50 IPS |
|
|
Object Detection (SP)
|
100% |
1014
80.4 IPS |
|
|
Object Detection (HP)
|
100% |
344
27.3 IPS |
|
|
Object Detection (Q)
|
58% |
1270
138.7 IPS |
|
|
Face Detection (SP)
|
100% |
1393
16.5 IPS |
|
|
Face Detection (HP)
|
100% |
656
7.80 IPS |
|
|
Face Detection (Q)
|
96% |
3203
38.2 IPS |
|
|
Depth Estimation (SP)
|
100% |
2847
21.9 IPS |
|
|
Depth Estimation (HP)
|
99% |
1044
8.04 IPS |
|
|
Depth Estimation (Q)
|
78% |
4151
33.1 IPS |
|
|
Style Transfer (SP)
|
100% |
5680
7.30 IPS |
|
|
Style Transfer (HP)
|
100% |
4824
6.20 IPS |
|
|
Style Transfer (Q)
|
87% |
5886
7.66 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
1115
41.2 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
957
35.4 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
2037
75.5 IPS |
|
|
Text Classification (SP)
|
100% |
1072
1.43 KIPS |
|
|
Text Classification (HP)
|
100% |
548
731.0 IPS |
|
|
Text Classification (Q)
|
97% |
915
1.23 KIPS |
|
|
Machine Translation (SP)
|
100% |
1029
17.7 IPS |
|
|
Machine Translation (HP)
|
100% |
406
7.00 IPS |
|
|
Machine Translation (Q)
|
68% |
1135
21.9 IPS |
