iPhone 15 Pro Max
Geekbench AI Score
3622
Single Precision Score
25880
Half Precision Score
35005
Quantized Score
Geekbench AI 1.5.0 for iOS AArch64
Result Information
| Upload Date | November 20 2025 01:37 AM |
| Views | 1 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | Neural Engine |
| Device | Apple A17 Pro |
| System Information | |
|---|---|
| Operating System | iOS 26.1 |
| 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% |
1561
290.4 IPS |
|
|
Image Classification (HP)
|
100% |
10624
1.98 KIPS |
|
|
Image Classification (Q)
|
97% |
13422
2.50 KIPS |
|
|
Image Segmentation (SP)
|
100% |
1531
24.8 IPS |
|
|
Image Segmentation (HP)
|
100% |
16442
266.5 IPS |
|
|
Image Segmentation (Q)
|
99% |
21071
341.6 IPS |
|
|
Pose Estimation (SP)
|
100% |
6827
7.97 IPS |
|
|
Pose Estimation (HP)
|
100% |
101970
119.0 IPS |
|
|
Pose Estimation (Q)
|
95% |
201215
235.8 IPS |
|
|
Object Detection (SP)
|
100% |
1608
127.5 IPS |
|
|
Object Detection (HP)
|
100% |
13410
1.06 KIPS |
|
|
Object Detection (Q)
|
91% |
15826
1.26 KIPS |
|
|
Face Detection (SP)
|
100% |
2937
34.9 IPS |
|
|
Face Detection (HP)
|
100% |
36645
435.4 IPS |
|
|
Face Detection (Q)
|
100% |
51305
609.6 IPS |
|
|
Depth Estimation (SP)
|
100% |
6367
49.1 IPS |
|
|
Depth Estimation (HP)
|
99% |
70957
546.7 IPS |
|
|
Depth Estimation (Q)
|
85% |
109813
858.6 IPS |
|
|
Style Transfer (SP)
|
100% |
19421
25.0 IPS |
|
|
Style Transfer (HP)
|
100% |
200339
257.5 IPS |
|
|
Style Transfer (Q)
|
96% |
238159
307.3 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
4240
156.5 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
28790
1.06 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
55872
2.06 KIPS |
|
|
Text Classification (SP)
|
100% |
3173
4.23 KIPS |
|
|
Text Classification (HP)
|
99% |
5676
7.58 KIPS |
|
|
Text Classification (Q)
|
93% |
5543
7.44 KIPS |
|
|
Machine Translation (SP)
|
100% |
3035
52.3 IPS |
|
|
Machine Translation (HP)
|
100% |
6629
114.2 IPS |
|
|
Machine Translation (Q)
|
98% |
7382
127.6 IPS |
