iPhone 15 Pro
Geekbench AI Score
3948
Single Precision Score
23186
Half Precision Score
30936
Quantized Score
Geekbench AI 1.1.0 for iOS AArch64
Result Information
| User | M91 |
| Upload Date | September 10 2024 11:42 AM |
| Views | 2 |
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% |
1676
311.7 IPS |
|
|
Image Classification (HP)
|
100% |
10960
2.04 KIPS |
|
|
Image Classification (Q)
|
97% |
15189
2.83 KIPS |
|
|
Image Segmentation (SP)
|
100% |
1626
26.4 IPS |
|
|
Image Segmentation (HP)
|
100% |
12952
210.0 IPS |
|
|
Image Segmentation (Q)
|
99% |
16015
259.6 IPS |
|
|
Pose Estimation (SP)
|
100% |
7734
9.02 IPS |
|
|
Pose Estimation (HP)
|
100% |
106092
123.8 IPS |
|
|
Pose Estimation (Q)
|
95% |
203745
238.8 IPS |
|
|
Object Detection (SP)
|
100% |
1795
142.4 IPS |
|
|
Object Detection (HP)
|
100% |
13886
1.10 KIPS |
|
|
Object Detection (Q)
|
91% |
19069
1.52 KIPS |
|
|
Face Detection (SP)
|
100% |
3249
38.6 IPS |
|
|
Face Detection (HP)
|
100% |
33725
400.7 IPS |
|
|
Face Detection (Q)
|
100% |
49221
584.9 IPS |
|
|
Depth Estimation (SP)
|
100% |
7181
55.3 IPS |
|
|
Depth Estimation (HP)
|
99% |
78507
604.9 IPS |
|
|
Depth Estimation (Q)
|
85% |
128734
1.01 KIPS |
|
|
Style Transfer (SP)
|
100% |
21146
27.2 IPS |
|
|
Style Transfer (HP)
|
100% |
138570
178.1 IPS |
|
|
Style Transfer (Q)
|
96% |
165515
213.6 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
4938
182.4 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
34445
1.27 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
55695
2.06 KIPS |
|
|
Text Classification (SP)
|
100% |
3182
4.25 KIPS |
|
|
Text Classification (HP)
|
100% |
2757
3.68 KIPS |
|
|
Text Classification (Q)
|
93% |
1975
2.65 KIPS |
|
|
Machine Translation (SP)
|
100% |
3141
54.1 IPS |
|
|
Machine Translation (HP)
|
100% |
6165
106.2 IPS |
|
|
Machine Translation (Q)
|
98% |
7364
127.3 IPS |
