Acer Nitro AN515-58
Geekbench AI Score
13540
Single Precision Score
20770
Half Precision Score
8964
Quantized Score
Geekbench AI 1.2.0 for Windows AVX2
Result Information
| User | dr3d |
| Upload Date | September 20 2025 11:57 AM |
| Views | 3 |
System Information
| AI Information | |
|---|---|
| Framework | ONNX |
| Backend | DirectML |
| Device | NVIDIA GeForce RTX 3070 Laptop GPU |
| System Information | |
|---|---|
| Operating System | Microsoft Windows 11 Home (64-bit) |
| Model | Acer Nitro AN515-58 |
| Motherboard | ADL Jimny_ADH |
| Power Plan | Balanced |
| CPU Information | |
|---|---|
| Name | Intel Core i7-12700H |
| Topology | 1 Processor, 14 Cores, 20 Threads |
| Identifier | GenuineIntel Family 6 Model 154 Stepping 3 |
| Base Frequency | 2.70 GHz |
| Cluster 1 | 6 Cores |
| Cluster 2 | 8 Cores |
| Memory Information | |
|---|---|
| Size | 32.00 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
5826
1.08 KIPS |
|
|
Image Classification (HP)
|
99% |
8532
1.59 KIPS |
|
|
Image Classification (Q)
|
100% |
4415
821.0 IPS |
|
|
Image Segmentation (SP)
|
100% |
9061
146.9 IPS |
|
|
Image Segmentation (HP)
|
100% |
11419
185.1 IPS |
|
|
Image Segmentation (Q)
|
98% |
7063
114.8 IPS |
|
|
Pose Estimation (SP)
|
100% |
82015
95.7 IPS |
|
|
Pose Estimation (HP)
|
100% |
224256
261.7 IPS |
|
|
Pose Estimation (Q)
|
96% |
62768
73.5 IPS |
|
|
Object Detection (SP)
|
100% |
5492
435.6 IPS |
|
|
Object Detection (HP)
|
100% |
8481
672.7 IPS |
|
|
Object Detection (Q)
|
85% |
4379
352.5 IPS |
|
|
Face Detection (SP)
|
100% |
17554
208.6 IPS |
|
|
Face Detection (HP)
|
100% |
19953
237.1 IPS |
|
|
Face Detection (Q)
|
97% |
10798
128.8 IPS |
|
|
Depth Estimation (SP)
|
100% |
33978
261.8 IPS |
|
|
Depth Estimation (HP)
|
99% |
55083
424.4 IPS |
|
|
Depth Estimation (Q)
|
77% |
25206
201.7 IPS |
|
|
Style Transfer (SP)
|
100% |
130560
167.8 IPS |
|
|
Style Transfer (HP)
|
100% |
303354
390.0 IPS |
|
|
Style Transfer (Q)
|
98% |
105968
136.6 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
21667
800.0 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
31605
1.17 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
14145
523.8 IPS |
|
|
Text Classification (SP)
|
100% |
2561
3.42 KIPS |
|
|
Text Classification (HP)
|
99% |
3340
4.46 KIPS |
|
|
Text Classification (Q)
|
97% |
1008
1.35 KIPS |
|
|
Machine Translation (SP)
|
100% |
2017
34.8 IPS |
|
|
Machine Translation (HP)
|
100% |
2291
39.5 IPS |
|
|
Machine Translation (Q)
|
70% |
951
17.8 IPS |
