MacBook Pro (13-inch, 2022)
Geekbench ML Score
9028
Core ML Neural Engine Inference Score
Geekbench ML 0.6.0 for macOS AArch64
Result Information
| Upload Date | January 19 2025 09:21 PM |
| Views | 4 |
System Information
| System Information | |
|---|---|
| Operating System | macOS 15.3 (Build 24D5055b) |
| Model | MacBook Pro (13-inch, 2022) |
| Model ID | Mac14,7 |
| Motherboard | Mac14,7 |
| CPU Information | |
|---|---|
| Name | Apple M2 |
| Topology | 1 Processor, 8 Cores |
| Identifier | Apple M2 |
| Base Frequency | 3.46 GHz |
| Cluster 1 | 4 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 | 8.00 GB |
| Inference Information | |
|---|---|
| Framework | Core ML |
| Backend | Neural Engine |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
3352
627.3 IPS |
|
|
Image Classification (F16)
|
100% |
10372
1.94 KIPS |
|
|
Image Classification (I8)
|
99% |
11777
2.20 KIPS |
|
|
Image Segmentation (F32)
|
100% |
1245
20.8 IPS |
|
|
Image Segmentation (F16)
|
100% |
1717
28.7 IPS |
|
|
Image Segmentation (I8)
|
100% |
1858
31.0 IPS |
|
|
Pose Estimation (F32)
|
100% |
19524
23.6 IPS |
|
|
Pose Estimation (F16)
|
100% |
66150
80.1 IPS |
|
|
Pose Estimation (I8)
|
100% |
84885
102.8 IPS |
|
|
Object Detection (F32)
|
100% |
2628
196.2 IPS |
|
|
Object Detection (F16)
|
100% |
5134
383.3 IPS |
|
|
Object Detection (I8)
|
97% |
1782
133.0 IPS |
|
|
Face Detection (F32)
|
100% |
7092
84.3 IPS |
|
|
Face Detection (F16)
|
97% |
17895
212.8 IPS |
|
|
Face Detection (I8)
|
96% |
19210
228.4 IPS |
|
|
Depth Estimation (F32)
|
100% |
15893
123.3 IPS |
|
|
Depth Estimation (F16)
|
100% |
51264
397.6 IPS |
|
|
Depth Estimation (I8)
|
37% |
39845
309.0 IPS |
|
|
Style Transfer (F32)
|
100% |
37440
49.2 IPS |
|
|
Style Transfer (F16)
|
100% |
139692
183.8 IPS |
|
|
Style Transfer (I8)
|
100% |
148824
195.8 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
10033
358.3 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
33051
1.18 KIPS |
|
|
Image Super-Resolution (I8)
|
100% |
35661
1.27 KIPS |
|
|
Text Classification (F32)
|
100% |
2054
2.95 KIPS |
|
|
Text Classification (F16)
|
100% |
3387
4.87 KIPS |
|
|
Text Classification (I8)
|
96% |
3422
4.92 KIPS |
|
|
Machine Translation (F32)
|
100% |
701
12.9 IPS |
|
|
Machine Translation (F16)
|
100% |
1358
25.0 IPS |
|
|
Machine Translation (I8)
|
99% |
659
12.1 IPS |
