MacBook Pro (13-inch, 2022)
Geekbench ML Score
9338
Core ML Neural Engine Inference Score
Geekbench ML 0.6.0 for macOS AArch64
Result Information
| Upload Date | March 20 2025 05:54 PM |
| Views | 7 |
System Information
| System Information | |
|---|---|
| Operating System | macOS 15.4 (Build 24E5238a) |
| 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 | 3.47 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% |
3354
627.6 IPS |
|
|
Image Classification (F16)
|
100% |
10316
1.93 KIPS |
|
|
Image Classification (I8)
|
99% |
10406
1.95 KIPS |
|
|
Image Segmentation (F32)
|
100% |
1453
24.3 IPS |
|
|
Image Segmentation (F16)
|
100% |
1910
31.9 IPS |
|
|
Image Segmentation (I8)
|
100% |
1945
32.5 IPS |
|
|
Pose Estimation (F32)
|
100% |
22845
27.7 IPS |
|
|
Pose Estimation (F16)
|
100% |
95110
115.2 IPS |
|
|
Pose Estimation (I8)
|
100% |
96501
116.9 IPS |
|
|
Object Detection (F32)
|
100% |
2263
169.0 IPS |
|
|
Object Detection (F16)
|
100% |
5464
407.9 IPS |
|
|
Object Detection (I8)
|
97% |
2810
209.8 IPS |
|
|
Face Detection (F32)
|
100% |
8860
105.3 IPS |
|
|
Face Detection (F16)
|
97% |
18900
224.7 IPS |
|
|
Face Detection (I8)
|
96% |
19134
227.5 IPS |
|
|
Depth Estimation (F32)
|
100% |
16026
124.3 IPS |
|
|
Depth Estimation (F16)
|
100% |
45625
353.8 IPS |
|
|
Depth Estimation (I8)
|
37% |
46736
362.4 IPS |
|
|
Style Transfer (F32)
|
100% |
34370
45.2 IPS |
|
|
Style Transfer (F16)
|
100% |
147470
194.0 IPS |
|
|
Style Transfer (I8)
|
100% |
148012
194.7 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
3941
140.8 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
32506
1.16 KIPS |
|
|
Image Super-Resolution (I8)
|
100% |
32089
1.15 KIPS |
|
|
Text Classification (F32)
|
100% |
1736
2.50 KIPS |
|
|
Text Classification (F16)
|
100% |
3070
4.41 KIPS |
|
|
Text Classification (I8)
|
96% |
3410
4.90 KIPS |
|
|
Machine Translation (F32)
|
100% |
1030
19.0 IPS |
|
|
Machine Translation (F16)
|
100% |
1397
25.7 IPS |
|
|
Machine Translation (I8)
|
99% |
1027
18.9 IPS |
