MacBook Pro (13-inch, 2022)
Geekbench ML Score
9586
Core ML Neural Engine Inference Score
Geekbench ML 0.6.0 for macOS AArch64
Result Information
| Upload Date | March 13 2025 06:25 PM |
| Views | 10 |
System Information
| System Information | |
|---|---|
| Operating System | macOS 15.4 (Build 24E5228e) |
| 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 | 3.18 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% |
3278
613.4 IPS |
|
|
Image Classification (F16)
|
100% |
10438
1.95 KIPS |
|
|
Image Classification (I8)
|
99% |
10992
2.06 KIPS |
|
|
Image Segmentation (F32)
|
100% |
1502
25.1 IPS |
|
|
Image Segmentation (F16)
|
100% |
1994
33.3 IPS |
|
|
Image Segmentation (I8)
|
100% |
2005
33.5 IPS |
|
|
Pose Estimation (F32)
|
100% |
23190
28.1 IPS |
|
|
Pose Estimation (F16)
|
100% |
94401
114.3 IPS |
|
|
Pose Estimation (I8)
|
100% |
96434
116.8 IPS |
|
|
Object Detection (F32)
|
100% |
2015
150.4 IPS |
|
|
Object Detection (F16)
|
100% |
5465
408.0 IPS |
|
|
Object Detection (I8)
|
97% |
2775
207.2 IPS |
|
|
Face Detection (F32)
|
100% |
9063
107.8 IPS |
|
|
Face Detection (F16)
|
97% |
19304
229.5 IPS |
|
|
Face Detection (I8)
|
96% |
20118
239.2 IPS |
|
|
Depth Estimation (F32)
|
100% |
16087
124.8 IPS |
|
|
Depth Estimation (F16)
|
100% |
48315
374.7 IPS |
|
|
Depth Estimation (I8)
|
37% |
48866
379.0 IPS |
|
|
Style Transfer (F32)
|
100% |
40189
52.9 IPS |
|
|
Style Transfer (F16)
|
100% |
124005
163.1 IPS |
|
|
Style Transfer (I8)
|
100% |
150252
197.6 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
7350
262.5 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
35173
1.26 KIPS |
|
|
Image Super-Resolution (I8)
|
100% |
19160
684.3 IPS |
|
|
Text Classification (F32)
|
100% |
2072
2.98 KIPS |
|
|
Text Classification (F16)
|
100% |
3501
5.03 KIPS |
|
|
Text Classification (I8)
|
96% |
3376
4.85 KIPS |
|
|
Machine Translation (F32)
|
100% |
1072
19.7 IPS |
|
|
Machine Translation (F16)
|
100% |
1401
25.8 IPS |
|
|
Machine Translation (I8)
|
99% |
1061
19.5 IPS |
