MacBook Pro (13-inch, 2022)
Geekbench ML Score
9575
Core ML Neural Engine Inference Score
Geekbench ML 0.6.0 for macOS AArch64
Result Information
| Upload Date | August 08 2025 06:34 PM |
| Views | 7 |
System Information
| System Information | |
|---|---|
| Operating System | macOS 26.0 (Build 25A5327h) |
| 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
627.2 IPS |
|
|
Image Classification (F16)
|
100% |
10215
1.91 KIPS |
|
|
Image Classification (I8)
|
99% |
11499
2.15 KIPS |
|
|
Image Segmentation (F32)
|
100% |
1359
22.7 IPS |
|
|
Image Segmentation (F16)
|
100% |
2007
33.5 IPS |
|
|
Image Segmentation (I8)
|
100% |
1701
28.4 IPS |
|
|
Pose Estimation (F32)
|
100% |
21627
26.2 IPS |
|
|
Pose Estimation (F16)
|
100% |
94411
114.3 IPS |
|
|
Pose Estimation (I8)
|
100% |
89448
108.3 IPS |
|
|
Object Detection (F32)
|
100% |
1694
126.5 IPS |
|
|
Object Detection (F16)
|
100% |
5380
401.7 IPS |
|
|
Object Detection (I8)
|
97% |
2840
212.0 IPS |
|
|
Face Detection (F32)
|
100% |
9314
110.7 IPS |
|
|
Face Detection (F16)
|
97% |
19516
232.0 IPS |
|
|
Face Detection (I8)
|
96% |
19726
234.5 IPS |
|
|
Depth Estimation (F32)
|
100% |
16555
128.4 IPS |
|
|
Depth Estimation (F16)
|
100% |
51720
401.1 IPS |
|
|
Depth Estimation (I8)
|
37% |
49462
383.6 IPS |
|
|
Style Transfer (F32)
|
100% |
34931
45.9 IPS |
|
|
Style Transfer (F16)
|
100% |
149127
196.2 IPS |
|
|
Style Transfer (I8)
|
100% |
145457
191.3 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
7103
253.7 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
35629
1.27 KIPS |
|
|
Image Super-Resolution (I8)
|
100% |
33023
1.18 KIPS |
|
|
Text Classification (F32)
|
100% |
2121
3.05 KIPS |
|
|
Text Classification (F16)
|
100% |
3523
5.06 KIPS |
|
|
Text Classification (I8)
|
96% |
3516
5.05 KIPS |
|
|
Machine Translation (F32)
|
100% |
955
17.6 IPS |
|
|
Machine Translation (F16)
|
100% |
1398
25.7 IPS |
|
|
Machine Translation (I8)
|
99% |
934
17.2 IPS |
