iPhone 15 Pro
Geekbench AI Score
3911
Single Precision Score
24943
Half Precision Score
34973
Quantized Score
Geekbench AI 1.1.0 for iOS AArch64
Result Information
| User | calvinh |
| Upload Date | November 02 2024 09:18 PM |
| Views | 1 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | Neural Engine |
| Device | Apple A17 Pro |
| System Information | |
|---|---|
| Operating System | iOS 18.1 |
| 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% |
1688
313.9 IPS |
|
|
Image Classification (HP)
|
100% |
10928
2.03 KIPS |
|
|
Image Classification (Q)
|
97% |
15293
2.85 KIPS |
|
|
Image Segmentation (SP)
|
100% |
1600
25.9 IPS |
|
|
Image Segmentation (HP)
|
100% |
15809
256.3 IPS |
|
|
Image Segmentation (Q)
|
99% |
20915
339.1 IPS |
|
|
Pose Estimation (SP)
|
100% |
7728
9.02 IPS |
|
|
Pose Estimation (HP)
|
100% |
105902
123.6 IPS |
|
|
Pose Estimation (Q)
|
95% |
203317
238.3 IPS |
|
|
Object Detection (SP)
|
100% |
1788
141.8 IPS |
|
|
Object Detection (HP)
|
100% |
13429
1.07 KIPS |
|
|
Object Detection (Q)
|
91% |
19031
1.52 KIPS |
|
|
Face Detection (SP)
|
100% |
3220
38.3 IPS |
|
|
Face Detection (HP)
|
100% |
35504
421.9 IPS |
|
|
Face Detection (Q)
|
100% |
51466
611.5 IPS |
|
|
Depth Estimation (SP)
|
100% |
6980
53.8 IPS |
|
|
Depth Estimation (HP)
|
99% |
79302
611.0 IPS |
|
|
Depth Estimation (Q)
|
85% |
127321
995.5 IPS |
|
|
Style Transfer (SP)
|
100% |
20608
26.5 IPS |
|
|
Style Transfer (HP)
|
100% |
201089
258.5 IPS |
|
|
Style Transfer (Q)
|
96% |
247476
319.4 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
4856
179.3 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
34242
1.26 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
58626
2.16 KIPS |
|
|
Text Classification (SP)
|
100% |
3188
4.25 KIPS |
|
|
Text Classification (HP)
|
100% |
3073
4.10 KIPS |
|
|
Text Classification (Q)
|
93% |
3127
4.20 KIPS |
|
|
Machine Translation (SP)
|
100% |
3134
54.0 IPS |
|
|
Machine Translation (HP)
|
100% |
6369
109.7 IPS |
|
|
Machine Translation (Q)
|
98% |
7440
128.6 IPS |
