iPhone 15 Pro Max
Geekbench AI Score
3846
Single Precision Score
25212
Half Precision Score
34687
Quantized Score
Geekbench AI 1.5.0 for iOS AArch64
Result Information
| Upload Date | October 25 2025 03:04 AM |
| Views | 2 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | Neural Engine |
| Device | Apple A17 Pro |
| System Information | |
|---|---|
| Operating System | iOS 26.0.1 |
| 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% |
1588
295.3 IPS |
|
|
Image Classification (HP)
|
100% |
12194
2.27 KIPS |
|
|
Image Classification (Q)
|
97% |
13762
2.57 KIPS |
|
|
Image Segmentation (SP)
|
100% |
1563
25.3 IPS |
|
|
Image Segmentation (HP)
|
100% |
15547
252.0 IPS |
|
|
Image Segmentation (Q)
|
99% |
21322
345.6 IPS |
|
|
Pose Estimation (SP)
|
100% |
7663
8.94 IPS |
|
|
Pose Estimation (HP)
|
100% |
104392
121.8 IPS |
|
|
Pose Estimation (Q)
|
95% |
199698
234.1 IPS |
|
|
Object Detection (SP)
|
100% |
1677
133.0 IPS |
|
|
Object Detection (HP)
|
100% |
11744
931.5 IPS |
|
|
Object Detection (Q)
|
91% |
16484
1.32 KIPS |
|
|
Face Detection (SP)
|
100% |
3093
36.7 IPS |
|
|
Face Detection (HP)
|
100% |
33853
402.2 IPS |
|
|
Face Detection (Q)
|
100% |
50158
596.0 IPS |
|
|
Depth Estimation (SP)
|
100% |
7005
54.0 IPS |
|
|
Depth Estimation (HP)
|
99% |
70132
540.3 IPS |
|
|
Depth Estimation (Q)
|
85% |
119385
933.4 IPS |
|
|
Style Transfer (SP)
|
100% |
21327
27.4 IPS |
|
|
Style Transfer (HP)
|
100% |
203084
261.1 IPS |
|
|
Style Transfer (Q)
|
96% |
231596
298.9 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
4732
174.7 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
29864
1.10 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
51778
1.91 KIPS |
|
|
Text Classification (SP)
|
100% |
3247
4.33 KIPS |
|
|
Text Classification (HP)
|
99% |
5551
7.41 KIPS |
|
|
Text Classification (Q)
|
93% |
5580
7.49 KIPS |
|
|
Machine Translation (SP)
|
100% |
3134
54.0 IPS |
|
|
Machine Translation (HP)
|
100% |
5586
96.2 IPS |
|
|
Machine Translation (Q)
|
98% |
6516
112.6 IPS |
