iPhone 15 Pro Max
Geekbench AI Score
3895
Single Precision Score
26904
Half Precision Score
36492
Quantized Score
Geekbench AI 1.2.0 for iOS AArch64
Result Information
| Upload Date | June 19 2025 11:14 AM |
| Views | 1 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | Neural Engine |
| Device | Apple A17 Pro |
| System Information | |
|---|---|
| Operating System | iOS 19.0 |
| 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 | 7.47 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
1671
310.8 IPS |
|
|
Image Classification (HP)
|
100% |
10575
1.97 KIPS |
|
|
Image Classification (Q)
|
97% |
14176
2.65 KIPS |
|
|
Image Segmentation (SP)
|
100% |
1593
25.8 IPS |
|
|
Image Segmentation (HP)
|
100% |
16587
268.9 IPS |
|
|
Image Segmentation (Q)
|
99% |
21190
343.5 IPS |
|
|
Pose Estimation (SP)
|
100% |
7882
9.20 IPS |
|
|
Pose Estimation (HP)
|
100% |
106621
124.4 IPS |
|
|
Pose Estimation (Q)
|
95% |
206071
241.5 IPS |
|
|
Object Detection (SP)
|
100% |
1759
139.5 IPS |
|
|
Object Detection (HP)
|
100% |
13896
1.10 KIPS |
|
|
Object Detection (Q)
|
91% |
17442
1.39 KIPS |
|
|
Face Detection (SP)
|
100% |
3176
37.7 IPS |
|
|
Face Detection (HP)
|
100% |
33683
400.2 IPS |
|
|
Face Detection (Q)
|
100% |
50203
596.5 IPS |
|
|
Depth Estimation (SP)
|
100% |
7005
54.0 IPS |
|
|
Depth Estimation (HP)
|
99% |
78109
601.8 IPS |
|
|
Depth Estimation (Q)
|
85% |
122367
956.7 IPS |
|
|
Style Transfer (SP)
|
100% |
21574
27.7 IPS |
|
|
Style Transfer (HP)
|
100% |
202985
260.9 IPS |
|
|
Style Transfer (Q)
|
96% |
255753
330.0 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
4846
178.9 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
34689
1.28 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
52211
1.93 KIPS |
|
|
Text Classification (SP)
|
100% |
2954
3.94 KIPS |
|
|
Text Classification (HP)
|
100% |
5130
6.85 KIPS |
|
|
Text Classification (Q)
|
93% |
5096
6.84 KIPS |
|
|
Machine Translation (SP)
|
100% |
3177
54.7 IPS |
|
|
Machine Translation (HP)
|
100% |
8047
138.6 IPS |
|
|
Machine Translation (Q)
|
98% |
9280
160.4 IPS |
