iPhone 12 Pro Max
Geekbench ML Score
3850
Core ML Neural Engine Inference Score
Geekbench ML 0.6.0 for iOS AArch64
Result Information
| Upload Date | January 05 2025 09:03 AM |
| Views | 3 |
System Information
| System Information | |
|---|---|
| Operating System | iOS 16.0.3 |
| Model | iPhone 12 Pro Max |
| Model ID | iPhone13,4 |
| Motherboard | D54pAP |
| CPU Information | |
|---|---|
| Name | Apple A14 Bionic |
| Topology | 1 Processor, 6 Cores |
| Identifier | ARM |
| Base Frequency | 2.99 GHz |
| Cluster 1 | 2 Cores |
| Cluster 2 | 4 Cores |
| L1 Instruction Cache | 128 KB x 1 |
| L1 Data Cache | 64.0 KB x 1 |
| L2 Cache | 4.00 MB x 1 |
| Memory Information | |
|---|---|
| Size | 5.54 GB |
| Inference Information | |
|---|---|
| Framework | Core ML |
| Backend | Neural Engine |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
380
71.2 IPS |
|
|
Image Classification (F16)
|
100% |
5214
975.6 IPS |
|
|
Image Classification (I8)
|
99% |
4338
811.7 IPS |
|
|
Image Segmentation (F32)
|
100% |
328
5.48 IPS |
|
|
Image Segmentation (F16)
|
100% |
1476
24.6 IPS |
|
|
Image Segmentation (I8)
|
100% |
1448
24.2 IPS |
|
|
Pose Estimation (F32)
|
100% |
5973
7.23 IPS |
|
|
Pose Estimation (F16)
|
100% |
60941
73.8 IPS |
|
|
Pose Estimation (I8)
|
100% |
59788
72.4 IPS |
|
|
Object Detection (F32)
|
100% |
661
49.4 IPS |
|
|
Object Detection (F16)
|
100% |
4457
332.7 IPS |
|
|
Object Detection (I8)
|
97% |
632
47.2 IPS |
|
|
Face Detection (F32)
|
100% |
3225
38.4 IPS |
|
|
Face Detection (F16)
|
97% |
7338
87.2 IPS |
|
|
Face Detection (I8)
|
96% |
7568
90.0 IPS |
|
|
Depth Estimation (F32)
|
100% |
5209
40.4 IPS |
|
|
Depth Estimation (F16)
|
100% |
34390
266.7 IPS |
|
|
Depth Estimation (I8)
|
99% |
34588
268.2 IPS |
|
|
Style Transfer (F32)
|
100% |
11493
15.1 IPS |
|
|
Style Transfer (F16)
|
100% |
78111
102.7 IPS |
|
|
Style Transfer (I8)
|
100% |
80572
106.0 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
1805
64.5 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
12025
429.5 IPS |
|
|
Image Super-Resolution (I8)
|
100% |
12031
429.7 IPS |
|
|
Text Classification (F32)
|
100% |
297
426.4 IPS |
|
|
Text Classification (F16)
|
100% |
886
1.27 KIPS |
|
|
Text Classification (I8)
|
96% |
878
1.26 KIPS |
|
|
Machine Translation (F32)
|
100% |
518
9.53 IPS |
|
|
Machine Translation (F16)
|
100% |
1161
21.4 IPS |
|
|
Machine Translation (I8)
|
99% |
518
9.53 IPS |
