Acer Nitro AN515-57
Geekbench AI Score
3443
Single Precision Score
1489
Half Precision Score
6662
Quantized Score
Geekbench AI 1.5.0 for Windows AVX2
Result Information
| Upload Date | November 13 2025 05:16 PM |
| Views | 2 |
System Information
| AI Information | |
|---|---|
| Framework | ONNX |
| Backend | CPU |
| Device | Intel Core i7-11800H |
| System Information | |
|---|---|
| Operating System | Microsoft Windows 11 Home (64-bit) |
| Model | Acer Nitro AN515-57 |
| Motherboard | TGL Scala_TLS |
| CPU Information | |
|---|---|
| Name | Intel Core i7-11800H |
| Topology | 1 Processor, 8 Cores, 16 Threads |
| Identifier | GenuineIntel Family 6 Model 141 Stepping 1 |
| Base Frequency | 2.30 GHz |
| Cluster 1 | 8 Cores |
| Memory Information | |
|---|---|
| Size | 16.00 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
3265
607.2 IPS |
|
|
Image Classification (HP)
|
100% |
538
100.1 IPS |
|
|
Image Classification (Q)
|
99% |
6543
1.22 KIPS |
|
|
Image Segmentation (SP)
|
100% |
1474
23.9 IPS |
|
|
Image Segmentation (HP)
|
100% |
840
13.6 IPS |
|
|
Image Segmentation (Q)
|
98% |
7328
119.2 IPS |
|
|
Pose Estimation (SP)
|
100% |
5757
6.72 IPS |
|
|
Pose Estimation (HP)
|
100% |
4414
5.15 IPS |
|
|
Pose Estimation (Q)
|
94% |
18032
21.1 IPS |
|
|
Object Detection (SP)
|
100% |
2762
219.1 IPS |
|
|
Object Detection (HP)
|
100% |
714
56.6 IPS |
|
|
Object Detection (Q)
|
86% |
6506
522.9 IPS |
|
|
Face Detection (SP)
|
100% |
3668
43.6 IPS |
|
|
Face Detection (HP)
|
100% |
1288
15.3 IPS |
|
|
Face Detection (Q)
|
97% |
8392
100.1 IPS |
|
|
Depth Estimation (SP)
|
100% |
7447
57.4 IPS |
|
|
Depth Estimation (HP)
|
99% |
1901
14.6 IPS |
|
|
Depth Estimation (Q)
|
78% |
12678
101.2 IPS |
|
|
Style Transfer (SP)
|
100% |
12841
16.5 IPS |
|
|
Style Transfer (HP)
|
100% |
10698
13.8 IPS |
|
|
Style Transfer (Q)
|
98% |
12218
15.8 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
2550
94.1 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
2156
79.6 IPS |
|
|
Image Super-Resolution (Q)
|
99% |
5752
213.0 IPS |
|
|
Text Classification (SP)
|
100% |
1749
2.33 KIPS |
|
|
Text Classification (HP)
|
100% |
889
1.19 KIPS |
|
|
Text Classification (Q)
|
97% |
1406
1.88 KIPS |
|
|
Machine Translation (SP)
|
100% |
1957
33.7 IPS |
|
|
Machine Translation (HP)
|
100% |
751
12.9 IPS |
|
|
Machine Translation (Q)
|
65% |
2913
58.5 IPS |
