MacBook Pro (13-inch, 2022)
Geekbench ML Score
10443
Core ML Neural Engine Inference Score
Geekbench ML 0.6.0 for macOS AArch64
Result Information
| Upload Date | March 10 2026 07:25 PM |
| Views | 6 |
System Information
| System Information | |
|---|---|
| Operating System | macOS 26.4 (Build 25E5233c) |
| 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 | 3.41 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% |
3510
656.8 IPS |
|
|
Image Classification (F16)
|
100% |
10360
1.94 KIPS |
|
|
Image Classification (I8)
|
99% |
11015
2.06 KIPS |
|
|
Image Segmentation (F32)
|
100% |
1376
23.0 IPS |
|
|
Image Segmentation (F16)
|
100% |
1964
32.8 IPS |
|
|
Image Segmentation (I8)
|
100% |
1959
32.7 IPS |
|
|
Pose Estimation (F32)
|
100% |
23489
28.4 IPS |
|
|
Pose Estimation (F16)
|
100% |
94479
114.4 IPS |
|
|
Pose Estimation (I8)
|
100% |
92424
111.9 IPS |
|
|
Object Detection (F32)
|
100% |
2550
190.4 IPS |
|
|
Object Detection (F16)
|
100% |
4981
371.9 IPS |
|
|
Object Detection (I8)
|
97% |
2573
192.1 IPS |
|
|
Face Detection (F32)
|
100% |
9750
115.9 IPS |
|
|
Face Detection (F16)
|
98% |
16127
191.8 IPS |
|
|
Face Detection (I8)
|
97% |
15957
189.7 IPS |
|
|
Depth Estimation (F32)
|
100% |
16272
126.2 IPS |
|
|
Depth Estimation (F16)
|
100% |
63396
491.6 IPS |
|
|
Depth Estimation (I8)
|
37% |
70223
544.6 IPS |
|
|
Style Transfer (F32)
|
100% |
39984
52.6 IPS |
|
|
Style Transfer (F16)
|
100% |
144595
190.2 IPS |
|
|
Style Transfer (I8)
|
100% |
151926
199.8 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
6599
235.7 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
35479
1.27 KIPS |
|
|
Image Super-Resolution (I8)
|
100% |
33647
1.20 KIPS |
|
|
Text Classification (F32)
|
100% |
3679
5.29 KIPS |
|
|
Text Classification (F16)
|
100% |
5581
8.02 KIPS |
|
|
Text Classification (I8)
|
96% |
5726
8.23 KIPS |
|
|
Machine Translation (F32)
|
100% |
1142
21.0 IPS |
|
|
Machine Translation (F16)
|
100% |
1402
25.8 IPS |
|
|
Machine Translation (I8)
|
99% |
1091
20.1 IPS |
