MacBook Pro (13-inch, 2022)
Geekbench ML Score
8829
Core ML Neural Engine Inference Score
Geekbench ML 0.6.0 for macOS AArch64
Result Information
| Upload Date | January 05 2026 06:48 PM |
| Views | 7 |
System Information
| System Information | |
|---|---|
| Operating System | macOS 26.3 (Build 25D5087f) |
| 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% |
1581
295.8 IPS |
|
|
Image Classification (F16)
|
100% |
10474
1.96 KIPS |
|
|
Image Classification (I8)
|
99% |
11451
2.14 KIPS |
|
|
Image Segmentation (F32)
|
100% |
1303
21.8 IPS |
|
|
Image Segmentation (F16)
|
100% |
1864
31.1 IPS |
|
|
Image Segmentation (I8)
|
100% |
1483
24.8 IPS |
|
|
Pose Estimation (F32)
|
100% |
14618
17.7 IPS |
|
|
Pose Estimation (F16)
|
100% |
94464
114.4 IPS |
|
|
Pose Estimation (I8)
|
100% |
97081
117.6 IPS |
|
|
Object Detection (F32)
|
100% |
2759
206.0 IPS |
|
|
Object Detection (F16)
|
100% |
4594
343.0 IPS |
|
|
Object Detection (I8)
|
97% |
1613
120.4 IPS |
|
|
Face Detection (F32)
|
100% |
4709
56.0 IPS |
|
|
Face Detection (F16)
|
97% |
20278
241.1 IPS |
|
|
Face Detection (I8)
|
96% |
18966
225.5 IPS |
|
|
Depth Estimation (F32)
|
100% |
15577
120.8 IPS |
|
|
Depth Estimation (F16)
|
100% |
52363
406.1 IPS |
|
|
Depth Estimation (I8)
|
37% |
51715
401.1 IPS |
|
|
Style Transfer (F32)
|
100% |
39456
51.9 IPS |
|
|
Style Transfer (F16)
|
100% |
146003
192.1 IPS |
|
|
Style Transfer (I8)
|
100% |
146632
192.9 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
5766
205.9 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
35968
1.28 KIPS |
|
|
Image Super-Resolution (I8)
|
100% |
35993
1.29 KIPS |
|
|
Text Classification (F32)
|
100% |
2099
3.02 KIPS |
|
|
Text Classification (F16)
|
100% |
3427
4.93 KIPS |
|
|
Text Classification (I8)
|
96% |
3470
4.99 KIPS |
|
|
Machine Translation (F32)
|
100% |
858
15.8 IPS |
|
|
Machine Translation (F16)
|
100% |
1411
26.0 IPS |
|
|
Machine Translation (I8)
|
99% |
878
16.2 IPS |
