MacBook Pro (13-inch, 2022)
Geekbench ML Score
10105
Core ML Neural Engine Inference Score
Geekbench ML 0.6.0 for macOS AArch64
Result Information
| Upload Date | April 17 2026 09:00 PM |
| Views | 4 |
System Information
| System Information | |
|---|---|
| Operating System | macOS 26.5 (Build 25F5053d) |
| 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% |
2156
403.5 IPS |
|
|
Image Classification (F16)
|
100% |
10511
1.97 KIPS |
|
|
Image Classification (I8)
|
99% |
11514
2.15 KIPS |
|
|
Image Segmentation (F32)
|
100% |
1215
20.3 IPS |
|
|
Image Segmentation (F16)
|
100% |
1850
30.9 IPS |
|
|
Image Segmentation (I8)
|
100% |
1438
24.0 IPS |
|
|
Pose Estimation (F32)
|
100% |
22870
27.7 IPS |
|
|
Pose Estimation (F16)
|
100% |
94208
114.1 IPS |
|
|
Pose Estimation (I8)
|
100% |
97039
117.5 IPS |
|
|
Object Detection (F32)
|
100% |
2330
173.9 IPS |
|
|
Object Detection (F16)
|
100% |
4818
359.7 IPS |
|
|
Object Detection (I8)
|
97% |
2837
211.8 IPS |
|
|
Face Detection (F32)
|
100% |
9421
112.0 IPS |
|
|
Face Detection (F16)
|
98% |
20488
243.6 IPS |
|
|
Face Detection (I8)
|
97% |
20668
245.8 IPS |
|
|
Depth Estimation (F32)
|
100% |
15524
120.4 IPS |
|
|
Depth Estimation (F16)
|
100% |
49946
387.3 IPS |
|
|
Depth Estimation (I8)
|
37% |
65264
506.1 IPS |
|
|
Style Transfer (F32)
|
100% |
40040
52.7 IPS |
|
|
Style Transfer (F16)
|
100% |
143076
188.2 IPS |
|
|
Style Transfer (I8)
|
100% |
146954
193.3 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
5811
207.5 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
35755
1.28 KIPS |
|
|
Image Super-Resolution (I8)
|
100% |
36488
1.30 KIPS |
|
|
Text Classification (F32)
|
100% |
3670
5.28 KIPS |
|
|
Text Classification (F16)
|
100% |
5632
8.09 KIPS |
|
|
Text Classification (I8)
|
96% |
5750
8.26 KIPS |
|
|
Machine Translation (F32)
|
100% |
1038
19.1 IPS |
|
|
Machine Translation (F16)
|
100% |
1386
25.5 IPS |
|
|
Machine Translation (I8)
|
99% |
1106
20.3 IPS |
