iPhone 15 Pro
Geekbench AI Score
3634
Single Precision Score
26441
Half Precision Score
36861
Quantized Score
Geekbench AI 1.5.0 for iOS AArch64
Result Information
| User | calvinh |
| Upload Date | November 07 2025 05:11 AM |
| Views | 1 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | Neural Engine |
| Device | Apple A17 Pro |
| System Information | |
|---|---|
| Operating System | iOS 26.2 |
| 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 | 7.50 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
1550
288.3 IPS |
|
|
Image Classification (HP)
|
100% |
10535
1.96 KIPS |
|
|
Image Classification (Q)
|
97% |
15782
2.95 KIPS |
|
|
Image Segmentation (SP)
|
100% |
1551
25.1 IPS |
|
|
Image Segmentation (HP)
|
100% |
16447
266.6 IPS |
|
|
Image Segmentation (Q)
|
99% |
21439
347.5 IPS |
|
|
Pose Estimation (SP)
|
100% |
6832
7.97 IPS |
|
|
Pose Estimation (HP)
|
100% |
103857
121.2 IPS |
|
|
Pose Estimation (Q)
|
95% |
205624
241.0 IPS |
|
|
Object Detection (SP)
|
100% |
1614
128.0 IPS |
|
|
Object Detection (HP)
|
100% |
13679
1.09 KIPS |
|
|
Object Detection (Q)
|
91% |
18623
1.49 KIPS |
|
|
Face Detection (SP)
|
100% |
2683
31.9 IPS |
|
|
Face Detection (HP)
|
100% |
34852
414.1 IPS |
|
|
Face Detection (Q)
|
100% |
51419
611.0 IPS |
|
|
Depth Estimation (SP)
|
100% |
6385
49.2 IPS |
|
|
Depth Estimation (HP)
|
99% |
78531
605.0 IPS |
|
|
Depth Estimation (Q)
|
85% |
122922
961.1 IPS |
|
|
Style Transfer (SP)
|
100% |
19703
25.3 IPS |
|
|
Style Transfer (HP)
|
100% |
201424
258.9 IPS |
|
|
Style Transfer (Q)
|
96% |
245093
316.3 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
4351
160.7 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
34368
1.27 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
59388
2.19 KIPS |
|
|
Text Classification (SP)
|
100% |
3242
4.33 KIPS |
|
|
Text Classification (HP)
|
99% |
5525
7.37 KIPS |
|
|
Text Classification (Q)
|
93% |
5608
7.53 KIPS |
|
|
Machine Translation (SP)
|
100% |
3183
54.8 IPS |
|
|
Machine Translation (HP)
|
100% |
6483
111.7 IPS |
|
|
Machine Translation (Q)
|
98% |
6928
119.7 IPS |
