iPhone 15 Pro Max
Geekbench AI Score
3878
Single Precision Score
25408
Half Precision Score
35806
Quantized Score
Geekbench AI 1.2.0 for iOS AArch64
Result Information
| Upload Date | April 24 2025 04:57 PM |
| Views | 1 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | Neural Engine |
| Device | Apple A17 Pro |
| System Information | |
|---|---|
| Operating System | iOS 18.5 |
| Model | iPhone 15 Pro Max |
| Model ID | iPhone16,2 |
| Motherboard | D84AP |
| 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 | 7.48 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
1614
300.1 IPS |
|
|
Image Classification (HP)
|
100% |
10914
2.03 KIPS |
|
|
Image Classification (Q)
|
97% |
15517
2.90 KIPS |
|
|
Image Segmentation (SP)
|
100% |
1601
26.0 IPS |
|
|
Image Segmentation (HP)
|
100% |
16308
264.4 IPS |
|
|
Image Segmentation (Q)
|
99% |
21161
343.0 IPS |
|
|
Pose Estimation (SP)
|
100% |
7986
9.32 IPS |
|
|
Pose Estimation (HP)
|
100% |
106674
124.5 IPS |
|
|
Pose Estimation (Q)
|
95% |
206648
242.2 IPS |
|
|
Object Detection (SP)
|
100% |
1756
139.3 IPS |
|
|
Object Detection (HP)
|
100% |
13804
1.09 KIPS |
|
|
Object Detection (Q)
|
91% |
19189
1.53 KIPS |
|
|
Face Detection (SP)
|
100% |
3100
36.8 IPS |
|
|
Face Detection (HP)
|
100% |
36661
435.6 IPS |
|
|
Face Detection (Q)
|
100% |
52734
626.6 IPS |
|
|
Depth Estimation (SP)
|
100% |
6836
52.7 IPS |
|
|
Depth Estimation (HP)
|
99% |
78584
605.4 IPS |
|
|
Depth Estimation (Q)
|
85% |
128235
1.00 KIPS |
|
|
Style Transfer (SP)
|
100% |
21000
27.0 IPS |
|
|
Style Transfer (HP)
|
100% |
209259
269.0 IPS |
|
|
Style Transfer (Q)
|
96% |
256214
330.6 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
4784
176.6 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
33814
1.25 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
58508
2.16 KIPS |
|
|
Text Classification (SP)
|
100% |
3234
4.32 KIPS |
|
|
Text Classification (HP)
|
100% |
3232
4.31 KIPS |
|
|
Text Classification (Q)
|
93% |
3457
4.64 KIPS |
|
|
Machine Translation (SP)
|
100% |
3084
53.1 IPS |
|
|
Machine Translation (HP)
|
100% |
6495
111.9 IPS |
|
|
Machine Translation (Q)
|
98% |
7593
131.2 IPS |
