Acer Predator PH18-72
Geekbench AI Score
22646
Single Precision Score
34983
Half Precision Score
17457
Quantized Score
Geekbench AI 1.6.0 for Windows AVX2
Result Information
| Upload Date | January 01 2026 08:17 PM |
| Views | 5 |
System Information
| AI Information | |
|---|---|
| Framework | ONNX |
| Backend | DirectML |
| Device | NVIDIA GeForce RTX 4080 Laptop GPU |
| System Information | |
|---|---|
| Operating System | Microsoft Windows 11 Pro (64-bit) |
| Model | Acer Predator PH18-72 |
| Motherboard | RPL IONIQ_RTX |
| Power Plan | Zrwnowaony |
| CPU Information | |
|---|---|
| Name | Intel Core i9-14900HX |
| Topology | 1 Processor, 24 Cores, 32 Threads |
| Identifier | GenuineIntel Family 6 Model 183 Stepping 1 |
| Base Frequency | 2.20 GHz |
| Cluster 1 | 8 Cores |
| Cluster 2 | 16 Cores |
| Memory Information | |
|---|---|
| Size | 96.00 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
8782
1.63 KIPS |
|
|
Image Classification (HP)
|
99% |
13816
2.58 KIPS |
|
|
Image Classification (Q)
|
100% |
7679
1.43 KIPS |
|
|
Image Segmentation (SP)
|
100% |
16237
263.2 IPS |
|
|
Image Segmentation (HP)
|
100% |
20848
338.0 IPS |
|
|
Image Segmentation (Q)
|
98% |
14731
239.5 IPS |
|
|
Pose Estimation (SP)
|
100% |
125926
146.9 IPS |
|
|
Pose Estimation (HP)
|
100% |
318750
371.9 IPS |
|
|
Pose Estimation (Q)
|
96% |
106442
124.7 IPS |
|
|
Object Detection (SP)
|
100% |
10734
851.4 IPS |
|
|
Object Detection (HP)
|
100% |
16972
1.35 KIPS |
|
|
Object Detection (Q)
|
85% |
9122
734.4 IPS |
|
|
Face Detection (SP)
|
100% |
31076
369.3 IPS |
|
|
Face Detection (HP)
|
100% |
43235
513.7 IPS |
|
|
Face Detection (Q)
|
97% |
27094
323.1 IPS |
|
|
Depth Estimation (SP)
|
100% |
52570
405.0 IPS |
|
|
Depth Estimation (HP)
|
99% |
92198
712.3 IPS |
|
|
Depth Estimation (Q)
|
77% |
40555
325.3 IPS |
|
|
Style Transfer (SP)
|
100% |
245187
315.2 IPS |
|
|
Style Transfer (HP)
|
100% |
572527
736.0 IPS |
|
|
Style Transfer (Q)
|
98% |
214062
276.0 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
35371
1.31 KIPS |
|
|
Image Super-Resolution (HP)
|
100% |
47147
1.74 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
26439
979.0 IPS |
|
|
Text Classification (SP)
|
100% |
3092
4.13 KIPS |
|
|
Text Classification (HP)
|
99% |
3906
5.21 KIPS |
|
|
Text Classification (Q)
|
97% |
1753
2.35 KIPS |
|
|
Machine Translation (SP)
|
100% |
4202
72.4 IPS |
|
|
Machine Translation (HP)
|
100% |
4193
72.2 IPS |
|
|
Machine Translation (Q)
|
70% |
2196
41.2 IPS |
