iPhone 15 Pro
Geekbench AI Score
4001
Single Precision Score
24913
Half Precision Score
35391
Quantized Score
Geekbench AI 1.2.0 for iOS AArch64
Result Information
| User | DVB |
| Upload Date | December 16 2024 04:12 PM |
| Views | 3 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | Neural Engine |
| Device | Apple A17 Pro |
| System Information | |
|---|---|
| Operating System | iOS 18.1.1 |
| Model | iPhone 15 Pro |
| Model ID | iPhone16,1 |
| Motherboard | D83AP |
| CPU Information | |
|---|---|
| Name | Apple A17 Pro |
| Topology | 1 Processor, 6 Cores |
| Identifier | ARM |
| Base Frequency | 3.78 GHz |
| Cluster 1 | 2 Cores |
| Cluster 2 | 4 Cores |
| Memory Information | |
|---|---|
| Size | 7.51 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
1731
322.0 IPS |
|
|
Image Classification (HP)
|
100% |
10998
2.05 KIPS |
|
|
Image Classification (Q)
|
97% |
16230
3.03 KIPS |
|
|
Image Segmentation (SP)
|
100% |
1668
27.0 IPS |
|
|
Image Segmentation (HP)
|
100% |
15728
255.0 IPS |
|
|
Image Segmentation (Q)
|
99% |
20912
339.0 IPS |
|
|
Pose Estimation (SP)
|
100% |
7954
9.28 IPS |
|
|
Pose Estimation (HP)
|
100% |
105961
123.6 IPS |
|
|
Pose Estimation (Q)
|
95% |
203508
238.5 IPS |
|
|
Object Detection (SP)
|
100% |
1813
143.8 IPS |
|
|
Object Detection (HP)
|
100% |
13860
1.10 KIPS |
|
|
Object Detection (Q)
|
91% |
19284
1.54 KIPS |
|
|
Face Detection (SP)
|
100% |
3275
38.9 IPS |
|
|
Face Detection (HP)
|
100% |
34993
415.8 IPS |
|
|
Face Detection (Q)
|
100% |
51608
613.2 IPS |
|
|
Depth Estimation (SP)
|
100% |
7158
55.1 IPS |
|
|
Depth Estimation (HP)
|
99% |
78858
607.6 IPS |
|
|
Depth Estimation (Q)
|
85% |
128549
1.01 KIPS |
|
|
Style Transfer (SP)
|
100% |
21187
27.2 IPS |
|
|
Style Transfer (HP)
|
100% |
203896
262.1 IPS |
|
|
Style Transfer (Q)
|
96% |
248033
320.1 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
4959
183.1 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
34273
1.27 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
57859
2.14 KIPS |
|
|
Text Classification (SP)
|
100% |
3192
4.26 KIPS |
|
|
Text Classification (HP)
|
100% |
3010
4.02 KIPS |
|
|
Text Classification (Q)
|
93% |
3129
4.20 KIPS |
|
|
Machine Translation (SP)
|
100% |
3218
55.4 IPS |
|
|
Machine Translation (HP)
|
100% |
6248
107.6 IPS |
|
|
Machine Translation (Q)
|
98% |
7769
134.3 IPS |
