Hewlett-Packard 23-g116
Geekbench ML Score
1221
ONNX CPU Inference Score
Geekbench ML 0.6.0 for Windows AVX2
Result Information
| Upload Date | March 02 2026 09:55 PM |
| Views | 4 |
System Information
| System Information | |
|---|---|
| Operating System | Microsoft Windows 11 Home (64-bit) |
| Model | Hewlett-Packard 23-g116 |
| Motherboard | Hewlett-Packard 2B0D |
| Power Plan | Balanced |
| CPU Information | |
|---|---|
| Name | Intel Core i4-4690T |
| Topology | 1 Processor, 4 Cores |
| Identifier | GenuineIntel Family 6 Model 60 Stepping 3 |
| Base Frequency | 2.50 GHz |
| Cluster 1 | 4 Cores |
| L1 Instruction Cache | 32.0 KB x 2 |
| L1 Data Cache | 32.0 KB x 2 |
| L2 Cache | 256 KB x 2 |
| L3 Cache | 6.00 MB x 1 |
| Memory Information | |
|---|---|
| Size | 16.00 GB |
| Inference Information | |
|---|---|
| Framework | ONNX |
| Backend | CPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
737
137.8 IPS |
|
|
Image Classification (F16)
|
100% |
732
137.0 IPS |
|
|
Image Classification (I8)
|
97% |
833
155.8 IPS |
|
|
Image Segmentation (F32)
|
100% |
525
8.77 IPS |
|
|
Image Segmentation (F16)
|
100% |
508
8.48 IPS |
|
|
Image Segmentation (I8)
|
97% |
869
14.5 IPS |
|
|
Pose Estimation (F32)
|
100% |
2274
2.75 IPS |
|
|
Pose Estimation (F16)
|
100% |
2269
2.75 IPS |
|
|
Pose Estimation (I8)
|
100% |
2464
2.98 IPS |
|
|
Object Detection (F32)
|
100% |
689
51.4 IPS |
|
|
Object Detection (F16)
|
100% |
687
51.3 IPS |
|
|
Object Detection (I8)
|
60% |
638
47.6 IPS |
|
|
Face Detection (F32)
|
100% |
1065
12.7 IPS |
|
|
Face Detection (F16)
|
100% |
1059
12.6 IPS |
|
|
Face Detection (I8)
|
87% |
1573
18.7 IPS |
|
|
Depth Estimation (F32)
|
100% |
2392
18.6 IPS |
|
|
Depth Estimation (F16)
|
100% |
2429
18.8 IPS |
|
|
Depth Estimation (I8)
|
74% |
2789
21.6 IPS |
|
|
Style Transfer (F32)
|
100% |
5127
6.74 IPS |
|
|
Style Transfer (F16)
|
100% |
5133
6.75 IPS |
|
|
Style Transfer (I8)
|
85% |
4862
6.40 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
1043
37.2 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
1010
36.1 IPS |
|
|
Image Super-Resolution (I8)
|
97% |
1015
36.2 IPS |
|
|
Text Classification (F32)
|
100% |
758
1.09 KIPS |
|
|
Text Classification (F16)
|
100% |
749
1.08 KIPS |
|
|
Text Classification (I8)
|
94% |
562
808.3 IPS |
|
|
Machine Translation (F32)
|
100% |
877
16.1 IPS |
|
|
Machine Translation (F16)
|
100% |
889
16.4 IPS |
|
|
Machine Translation (I8)
|
67% |
1038
19.1 IPS |
