MacBook Pro (13-inch, 2022)
Geekbench ML Score
9262
Core ML Neural Engine Inference Score
Geekbench ML 0.6.0 for macOS AArch64
Result Information
| Upload Date | December 19 2025 07:53 PM |
| Views | 5 |
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 | 3.31 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% |
3463
648.0 IPS |
|
|
Image Classification (F16)
|
100% |
10152
1.90 KIPS |
|
|
Image Classification (I8)
|
99% |
11656
2.18 KIPS |
|
|
Image Segmentation (F32)
|
100% |
740
12.4 IPS |
|
|
Image Segmentation (F16)
|
100% |
1945
32.5 IPS |
|
|
Image Segmentation (I8)
|
100% |
1868
31.2 IPS |
|
|
Pose Estimation (F32)
|
100% |
23181
28.1 IPS |
|
|
Pose Estimation (F16)
|
100% |
94032
113.9 IPS |
|
|
Pose Estimation (I8)
|
100% |
93738
113.5 IPS |
|
|
Object Detection (F32)
|
100% |
2191
163.6 IPS |
|
|
Object Detection (F16)
|
100% |
4775
356.5 IPS |
|
|
Object Detection (I8)
|
97% |
2875
214.6 IPS |
|
|
Face Detection (F32)
|
100% |
9565
113.7 IPS |
|
|
Face Detection (F16)
|
97% |
17834
212.1 IPS |
|
|
Face Detection (I8)
|
96% |
15295
181.9 IPS |
|
|
Depth Estimation (F32)
|
100% |
12731
98.7 IPS |
|
|
Depth Estimation (F16)
|
100% |
47497
368.3 IPS |
|
|
Depth Estimation (I8)
|
37% |
46510
360.7 IPS |
|
|
Style Transfer (F32)
|
100% |
40558
53.4 IPS |
|
|
Style Transfer (F16)
|
100% |
145898
191.9 IPS |
|
|
Style Transfer (I8)
|
100% |
135425
178.1 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
7167
256.0 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
36925
1.32 KIPS |
|
|
Image Super-Resolution (I8)
|
100% |
35048
1.25 KIPS |
|
|
Text Classification (F32)
|
100% |
2118
3.04 KIPS |
|
|
Text Classification (F16)
|
100% |
3505
5.04 KIPS |
|
|
Text Classification (I8)
|
96% |
3478
5.00 KIPS |
|
|
Machine Translation (F32)
|
100% |
908
16.7 IPS |
|
|
Machine Translation (F16)
|
100% |
1373
25.3 IPS |
|
|
Machine Translation (I8)
|
99% |
846
15.6 IPS |
