MacBook Pro (13-inch, 2022)
Geekbench ML Score
9713
Core ML Neural Engine Inference Score
Geekbench ML 0.6.0 for macOS AArch64
Result Information
| Upload Date | October 15 2025 02:43 PM |
| Views | 9 |
System Information
| System Information | |
|---|---|
| Operating System | macOS 26.1 (Build 25B5062e) |
| 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 | 3.47 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% |
2933
548.9 IPS |
|
|
Image Classification (F16)
|
100% |
10541
1.97 KIPS |
|
|
Image Classification (I8)
|
99% |
11616
2.17 KIPS |
|
|
Image Segmentation (F32)
|
100% |
1543
25.8 IPS |
|
|
Image Segmentation (F16)
|
100% |
1954
32.6 IPS |
|
|
Image Segmentation (I8)
|
100% |
2011
33.6 IPS |
|
|
Pose Estimation (F32)
|
100% |
23734
28.7 IPS |
|
|
Pose Estimation (F16)
|
100% |
92341
111.8 IPS |
|
|
Pose Estimation (I8)
|
100% |
93673
113.4 IPS |
|
|
Object Detection (F32)
|
100% |
2862
213.6 IPS |
|
|
Object Detection (F16)
|
100% |
5430
405.4 IPS |
|
|
Object Detection (I8)
|
97% |
2868
214.1 IPS |
|
|
Face Detection (F32)
|
100% |
6900
82.0 IPS |
|
|
Face Detection (F16)
|
97% |
18955
225.4 IPS |
|
|
Face Detection (I8)
|
96% |
17717
210.7 IPS |
|
|
Depth Estimation (F32)
|
100% |
16740
129.8 IPS |
|
|
Depth Estimation (F16)
|
100% |
60108
466.1 IPS |
|
|
Depth Estimation (I8)
|
37% |
66056
512.3 IPS |
|
|
Style Transfer (F32)
|
100% |
40996
53.9 IPS |
|
|
Style Transfer (F16)
|
100% |
143836
189.2 IPS |
|
|
Style Transfer (I8)
|
100% |
150716
198.3 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
7158
255.6 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
37111
1.33 KIPS |
|
|
Image Super-Resolution (I8)
|
100% |
36078
1.29 KIPS |
|
|
Text Classification (F32)
|
100% |
2141
3.08 KIPS |
|
|
Text Classification (F16)
|
100% |
3440
4.94 KIPS |
|
|
Text Classification (I8)
|
96% |
3503
5.03 KIPS |
|
|
Machine Translation (F32)
|
0% |
667
12.3 IPS |
|
|
Machine Translation (F16)
|
100% |
1381
25.4 IPS |
|
|
Machine Translation (I8)
|
0% |
674
12.4 IPS |
