MacBook Pro (13-inch, 2022)
Geekbench ML Score
9356
Core ML Neural Engine Inference Score
Geekbench ML 0.6.0 for macOS AArch64
Result Information
| Upload Date | February 04 2026 07:31 PM |
| Views | 4 |
System Information
| System Information | |
|---|---|
| Operating System | macOS 26.3 (Build 25D5112c) |
| 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 | 3.30 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% |
1969
368.4 IPS |
|
|
Image Classification (F16)
|
100% |
10117
1.89 KIPS |
|
|
Image Classification (I8)
|
99% |
11292
2.11 KIPS |
|
|
Image Segmentation (F32)
|
100% |
1245
20.8 IPS |
|
|
Image Segmentation (F16)
|
100% |
1896
31.7 IPS |
|
|
Image Segmentation (I8)
|
100% |
1661
27.7 IPS |
|
|
Pose Estimation (F32)
|
100% |
22036
26.7 IPS |
|
|
Pose Estimation (F16)
|
100% |
93202
112.9 IPS |
|
|
Pose Estimation (I8)
|
100% |
80912
98.0 IPS |
|
|
Object Detection (F32)
|
100% |
1315
98.2 IPS |
|
|
Object Detection (F16)
|
100% |
6135
458.0 IPS |
|
|
Object Detection (I8)
|
97% |
2833
211.5 IPS |
|
|
Face Detection (F32)
|
100% |
9365
111.4 IPS |
|
|
Face Detection (F16)
|
97% |
19127
227.4 IPS |
|
|
Face Detection (I8)
|
96% |
19222
228.6 IPS |
|
|
Depth Estimation (F32)
|
100% |
16094
124.8 IPS |
|
|
Depth Estimation (F16)
|
100% |
53838
417.5 IPS |
|
|
Depth Estimation (I8)
|
37% |
47555
368.8 IPS |
|
|
Style Transfer (F32)
|
100% |
40239
52.9 IPS |
|
|
Style Transfer (F16)
|
100% |
145891
191.9 IPS |
|
|
Style Transfer (I8)
|
100% |
136265
179.2 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
7302
260.8 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
33719
1.20 KIPS |
|
|
Image Super-Resolution (I8)
|
100% |
34936
1.25 KIPS |
|
|
Text Classification (F32)
|
100% |
2109
3.03 KIPS |
|
|
Text Classification (F16)
|
100% |
3561
5.12 KIPS |
|
|
Text Classification (I8)
|
96% |
3495
5.02 KIPS |
|
|
Machine Translation (F32)
|
100% |
1124
20.7 IPS |
|
|
Machine Translation (F16)
|
100% |
1377
25.3 IPS |
|
|
Machine Translation (I8)
|
99% |
1024
18.8 IPS |
