iPhone 15 Pro
Geekbench AI Score
4034
Single Precision Score
24693
Half Precision Score
34365
Quantized Score
Geekbench AI 1.1.0 for iOS AArch64
Result Information
| User | lafcadio |
| Upload Date | October 02 2024 05:00 PM |
| Views | 8 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | Neural Engine |
| Device | Apple A17 Pro |
| System Information | |
|---|---|
| Operating System | iOS 18.0 |
| 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% |
1710
317.9 IPS |
|
|
Image Classification (HP)
|
100% |
11509
2.14 KIPS |
|
|
Image Classification (Q)
|
97% |
15559
2.90 KIPS |
|
|
Image Segmentation (SP)
|
100% |
1718
27.8 IPS |
|
|
Image Segmentation (HP)
|
100% |
12718
206.2 IPS |
|
|
Image Segmentation (Q)
|
99% |
16002
259.4 IPS |
|
|
Pose Estimation (SP)
|
100% |
8140
9.50 IPS |
|
|
Pose Estimation (HP)
|
100% |
107939
125.9 IPS |
|
|
Pose Estimation (Q)
|
95% |
206364
241.9 IPS |
|
|
Object Detection (SP)
|
100% |
1793
142.2 IPS |
|
|
Object Detection (HP)
|
100% |
13646
1.08 KIPS |
|
|
Object Detection (Q)
|
91% |
19440
1.55 KIPS |
|
|
Face Detection (SP)
|
100% |
3205
38.1 IPS |
|
|
Face Detection (HP)
|
100% |
33679
400.2 IPS |
|
|
Face Detection (Q)
|
100% |
49535
588.6 IPS |
|
|
Depth Estimation (SP)
|
100% |
7219
55.6 IPS |
|
|
Depth Estimation (HP)
|
99% |
79471
612.3 IPS |
|
|
Depth Estimation (Q)
|
85% |
129831
1.02 KIPS |
|
|
Style Transfer (SP)
|
100% |
21664
27.8 IPS |
|
|
Style Transfer (HP)
|
100% |
205458
264.1 IPS |
|
|
Style Transfer (Q)
|
96% |
253703
327.4 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
5052
186.6 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
33824
1.25 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
58756
2.17 KIPS |
|
|
Text Classification (SP)
|
100% |
3244
4.33 KIPS |
|
|
Text Classification (HP)
|
100% |
3430
4.58 KIPS |
|
|
Text Classification (Q)
|
93% |
3217
4.32 KIPS |
|
|
Machine Translation (SP)
|
100% |
3247
55.9 IPS |
|
|
Machine Translation (HP)
|
100% |
6128
105.6 IPS |
|
|
Machine Translation (Q)
|
98% |
7457
128.9 IPS |
