MacBook Pro (13-inch, 2022)
Geekbench ML Score
9018
Core ML Neural Engine Inference Score
Geekbench ML 0.6.0 for macOS AArch64
Result Information
| Upload Date | August 20 2025 06:38 PM |
| Views | 6 |
System Information
| System Information | |
|---|---|
| Operating System | macOS 26.0 (Build 25A5346a) |
| 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% |
2082
389.6 IPS |
|
|
Image Classification (F16)
|
100% |
10294
1.93 KIPS |
|
|
Image Classification (I8)
|
99% |
11284
2.11 KIPS |
|
|
Image Segmentation (F32)
|
100% |
1069
17.8 IPS |
|
|
Image Segmentation (F16)
|
100% |
1832
30.6 IPS |
|
|
Image Segmentation (I8)
|
100% |
1520
25.4 IPS |
|
|
Pose Estimation (F32)
|
100% |
22790
27.6 IPS |
|
|
Pose Estimation (F16)
|
100% |
93881
113.7 IPS |
|
|
Pose Estimation (I8)
|
100% |
96584
117.0 IPS |
|
|
Object Detection (F32)
|
100% |
1562
116.6 IPS |
|
|
Object Detection (F16)
|
100% |
4410
329.3 IPS |
|
|
Object Detection (I8)
|
97% |
1810
135.1 IPS |
|
|
Face Detection (F32)
|
100% |
9108
108.3 IPS |
|
|
Face Detection (F16)
|
97% |
20288
241.2 IPS |
|
|
Face Detection (I8)
|
96% |
19846
236.0 IPS |
|
|
Depth Estimation (F32)
|
100% |
15686
121.6 IPS |
|
|
Depth Estimation (F16)
|
100% |
52456
406.8 IPS |
|
|
Depth Estimation (I8)
|
37% |
58672
455.0 IPS |
|
|
Style Transfer (F32)
|
100% |
40386
53.1 IPS |
|
|
Style Transfer (F16)
|
100% |
129369
170.2 IPS |
|
|
Style Transfer (I8)
|
100% |
147225
193.7 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
5681
202.9 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
34288
1.22 KIPS |
|
|
Image Super-Resolution (I8)
|
100% |
34243
1.22 KIPS |
|
|
Text Classification (F32)
|
100% |
2104
3.02 KIPS |
|
|
Text Classification (F16)
|
100% |
3457
4.97 KIPS |
|
|
Text Classification (I8)
|
96% |
3441
4.95 KIPS |
|
|
Machine Translation (F32)
|
100% |
872
16.0 IPS |
|
|
Machine Translation (F16)
|
100% |
1388
25.5 IPS |
|
|
Machine Translation (I8)
|
99% |
884
16.3 IPS |
