iPhone 15 Pro Max
Geekbench AI Score
3904
Single Precision Score
6985
Half Precision Score
5673
Quantized Score
Geekbench AI 1.2.0 for iOS AArch64
Result Information
| Upload Date | April 13 2025 06:44 AM |
| Views | 2 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | CPU |
| Device | Apple A17 Pro |
| System Information | |
|---|---|
| Operating System | iOS 18.4 |
| 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% |
1628
302.8 IPS |
|
|
Image Classification (HP)
|
100% |
2995
556.9 IPS |
|
|
Image Classification (Q)
|
96% |
2042
381.4 IPS |
|
|
Image Segmentation (SP)
|
100% |
1622
26.3 IPS |
|
|
Image Segmentation (HP)
|
100% |
2454
39.8 IPS |
|
|
Image Segmentation (Q)
|
99% |
3020
49.0 IPS |
|
|
Pose Estimation (SP)
|
100% |
7971
9.30 IPS |
|
|
Pose Estimation (HP)
|
100% |
16544
19.3 IPS |
|
|
Pose Estimation (Q)
|
95% |
14139
16.6 IPS |
|
|
Object Detection (SP)
|
100% |
1761
139.7 IPS |
|
|
Object Detection (HP)
|
97% |
3324
264.7 IPS |
|
|
Object Detection (Q)
|
94% |
2360
188.1 IPS |
|
|
Face Detection (SP)
|
100% |
2988
35.5 IPS |
|
|
Face Detection (HP)
|
100% |
6623
78.7 IPS |
|
|
Face Detection (Q)
|
100% |
3770
44.8 IPS |
|
|
Depth Estimation (SP)
|
100% |
6841
52.7 IPS |
|
|
Depth Estimation (HP)
|
98% |
12894
99.7 IPS |
|
|
Depth Estimation (Q)
|
85% |
8933
69.8 IPS |
|
|
Style Transfer (SP)
|
100% |
21199
27.3 IPS |
|
|
Style Transfer (HP)
|
100% |
33915
43.6 IPS |
|
|
Style Transfer (Q)
|
96% |
27928
36.0 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
4840
178.7 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
5816
214.7 IPS |
|
|
Image Super-Resolution (Q)
|
99% |
4483
165.5 IPS |
|
|
Text Classification (SP)
|
100% |
3344
4.46 KIPS |
|
|
Text Classification (HP)
|
100% |
5895
7.87 KIPS |
|
|
Text Classification (Q)
|
93% |
5732
7.69 KIPS |
|
|
Machine Translation (SP)
|
100% |
3167
54.6 IPS |
|
|
Machine Translation (HP)
|
98% |
6891
119.1 IPS |
|
|
Machine Translation (Q)
|
98% |
6952
120.1 IPS |
