MacBook Pro (13-inch, 2022)
Geekbench ML Score
9301
Core ML Neural Engine Inference Score
Geekbench ML 0.6.0 for macOS AArch64
Result Information
| Upload Date | October 17 2025 04:27 PM |
| Views | 11 |
System Information
| System Information | |
|---|---|
| Operating System | macOS 26.1 (Build 25B5062e) |
| 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 | 3.08 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% |
2537
474.7 IPS |
|
|
Image Classification (F16)
|
100% |
9886
1.85 KIPS |
|
|
Image Classification (I8)
|
99% |
9438
1.77 KIPS |
|
|
Image Segmentation (F32)
|
100% |
1499
25.0 IPS |
|
|
Image Segmentation (F16)
|
100% |
1888
31.5 IPS |
|
|
Image Segmentation (I8)
|
100% |
1200
20.0 IPS |
|
|
Pose Estimation (F32)
|
100% |
23137
28.0 IPS |
|
|
Pose Estimation (F16)
|
100% |
92892
112.5 IPS |
|
|
Pose Estimation (I8)
|
100% |
89724
108.7 IPS |
|
|
Object Detection (F32)
|
100% |
2567
191.7 IPS |
|
|
Object Detection (F16)
|
100% |
5518
411.9 IPS |
|
|
Object Detection (I8)
|
97% |
2835
211.6 IPS |
|
|
Face Detection (F32)
|
100% |
8463
100.6 IPS |
|
|
Face Detection (F16)
|
97% |
20314
241.5 IPS |
|
|
Face Detection (I8)
|
96% |
20273
241.1 IPS |
|
|
Depth Estimation (F32)
|
100% |
16034
124.3 IPS |
|
|
Depth Estimation (F16)
|
100% |
51312
397.9 IPS |
|
|
Depth Estimation (I8)
|
37% |
55166
427.8 IPS |
|
|
Style Transfer (F32)
|
100% |
40497
53.3 IPS |
|
|
Style Transfer (F16)
|
100% |
147805
194.4 IPS |
|
|
Style Transfer (I8)
|
100% |
138329
182.0 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
8201
292.9 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
31356
1.12 KIPS |
|
|
Image Super-Resolution (I8)
|
100% |
32784
1.17 KIPS |
|
|
Text Classification (F32)
|
100% |
2136
3.07 KIPS |
|
|
Text Classification (F16)
|
100% |
3464
4.98 KIPS |
|
|
Text Classification (I8)
|
96% |
3495
5.02 KIPS |
|
|
Machine Translation (F32)
|
0% |
664
12.2 IPS |
|
|
Machine Translation (F16)
|
100% |
1379
25.4 IPS |
|
|
Machine Translation (I8)
|
0% |
700
12.9 IPS |
