Acer Nitro AN515-58
Geekbench AI Score
12371
Single Precision Score
19589
Half Precision Score
8473
Quantized Score
Geekbench AI 1.2.0 for Windows AVX2
Result Information
| User | dr3d |
| Upload Date | December 26 2024 12:31 AM |
| Views | 1 |
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% |
4529
842.2 IPS |
|
|
Image Classification (HP)
|
99% |
8219
1.53 KIPS |
|
|
Image Classification (Q)
|
100% |
3416
635.2 IPS |
|
|
Image Segmentation (SP)
|
100% |
6706
108.7 IPS |
|
|
Image Segmentation (HP)
|
100% |
10821
175.4 IPS |
|
|
Image Segmentation (Q)
|
98% |
6294
102.3 IPS |
|
|
Pose Estimation (SP)
|
100% |
75033
87.6 IPS |
|
|
Pose Estimation (HP)
|
100% |
224912
262.4 IPS |
|
|
Pose Estimation (Q)
|
96% |
63971
75.0 IPS |
|
|
Object Detection (SP)
|
100% |
5882
466.5 IPS |
|
|
Object Detection (HP)
|
100% |
8716
691.4 IPS |
|
|
Object Detection (Q)
|
85% |
4263
343.2 IPS |
|
|
Face Detection (SP)
|
100% |
12958
154.0 IPS |
|
|
Face Detection (HP)
|
100% |
17494
207.9 IPS |
|
|
Face Detection (Q)
|
97% |
10800
128.8 IPS |
|
|
Depth Estimation (SP)
|
100% |
33082
254.9 IPS |
|
|
Depth Estimation (HP)
|
99% |
56961
438.9 IPS |
|
|
Depth Estimation (Q)
|
77% |
22386
179.2 IPS |
|
|
Style Transfer (SP)
|
100% |
122362
157.3 IPS |
|
|
Style Transfer (HP)
|
100% |
263854
339.2 IPS |
|
|
Style Transfer (Q)
|
98% |
100083
129.1 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
23424
864.9 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
26014
960.6 IPS |
|
|
Image Super-Resolution (Q)
|
99% |
12803
474.1 IPS |
|
|
Text Classification (SP)
|
100% |
2525
3.37 KIPS |
|
|
Text Classification (HP)
|
99% |
3320
4.43 KIPS |
|
|
Text Classification (Q)
|
97% |
1125
1.51 KIPS |
|
|
Machine Translation (SP)
|
100% |
2019
34.8 IPS |
|
|
Machine Translation (HP)
|
100% |
2102
36.2 IPS |
|
|
Machine Translation (Q)
|
70% |
934
17.5 IPS |
