MacBook Pro (13-inch, 2022)
Geekbench ML Score
9528
Core ML Neural Engine Inference Score
Geekbench ML 0.6.0 for macOS AArch64
Result Information
| Upload Date | September 15 2025 06:18 PM |
| Views | 7 |
System Information
| System Information | |
|---|---|
| Operating System | macOS 26.0 (Build 25A353) |
| 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% |
3321
621.5 IPS |
|
|
Image Classification (F16)
|
100% |
10731
2.01 KIPS |
|
|
Image Classification (I8)
|
99% |
11706
2.19 KIPS |
|
|
Image Segmentation (F32)
|
100% |
1479
24.7 IPS |
|
|
Image Segmentation (F16)
|
100% |
1680
28.1 IPS |
|
|
Image Segmentation (I8)
|
100% |
1425
23.8 IPS |
|
|
Pose Estimation (F32)
|
100% |
23201
28.1 IPS |
|
|
Pose Estimation (F16)
|
100% |
74538
90.3 IPS |
|
|
Pose Estimation (I8)
|
100% |
82119
99.4 IPS |
|
|
Object Detection (F32)
|
100% |
2828
211.1 IPS |
|
|
Object Detection (F16)
|
100% |
5365
400.5 IPS |
|
|
Object Detection (I8)
|
97% |
2662
198.7 IPS |
|
|
Face Detection (F32)
|
100% |
9163
109.0 IPS |
|
|
Face Detection (F16)
|
97% |
17737
210.9 IPS |
|
|
Face Detection (I8)
|
96% |
20431
242.9 IPS |
|
|
Depth Estimation (F32)
|
100% |
16329
126.6 IPS |
|
|
Depth Estimation (F16)
|
100% |
48873
379.0 IPS |
|
|
Depth Estimation (I8)
|
37% |
46966
364.2 IPS |
|
|
Style Transfer (F32)
|
100% |
40892
53.8 IPS |
|
|
Style Transfer (F16)
|
100% |
132163
173.8 IPS |
|
|
Style Transfer (I8)
|
100% |
133252
175.3 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
7139
254.9 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
36492
1.30 KIPS |
|
|
Image Super-Resolution (I8)
|
100% |
33934
1.21 KIPS |
|
|
Text Classification (F32)
|
100% |
2079
2.99 KIPS |
|
|
Text Classification (F16)
|
100% |
3546
5.10 KIPS |
|
|
Text Classification (I8)
|
96% |
2709
3.89 KIPS |
|
|
Machine Translation (F32)
|
100% |
1098
20.2 IPS |
|
|
Machine Translation (F16)
|
100% |
1414
26.0 IPS |
|
|
Machine Translation (I8)
|
99% |
1127
20.7 IPS |
