MacBook Pro (14-inch, 2023)
Geekbench ML Score
9423
Core ML Neural Engine Inference Score
Geekbench ML 0.6.0 for macOS AArch64
Result Information
| Upload Date | May 08 2024 09:46 AM |
| Views | 2 |
System Information
| System Information | |
|---|---|
| Operating System | macOS 14.4.1 (Build 23E224) |
| Model | MacBook Pro (14-inch, 2023) |
| Model ID | Mac14,5 |
| Motherboard | Mac14,5 |
| CPU Information | |
|---|---|
| Name | Apple M2 Max |
| Topology | 1 Processor, 12 Cores |
| Identifier | Apple M2 Max |
| Base Frequency | 3.48 GHz |
| Cluster 1 | 8 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 | 32.00 GB |
| Inference Information | |
|---|---|
| Framework | Core ML |
| Backend | Neural Engine |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
5601
1.05 KIPS |
|
|
Image Classification (F16)
|
100% |
7174
1.34 KIPS |
|
|
Image Classification (I8)
|
99% |
7916
1.48 KIPS |
|
|
Image Segmentation (F32)
|
100% |
2198
36.7 IPS |
|
|
Image Segmentation (F16)
|
100% |
1883
31.4 IPS |
|
|
Image Segmentation (I8)
|
100% |
1872
31.3 IPS |
|
|
Pose Estimation (F32)
|
100% |
55373
67.1 IPS |
|
|
Pose Estimation (F16)
|
100% |
79780
96.6 IPS |
|
|
Pose Estimation (I8)
|
100% |
82480
99.9 IPS |
|
|
Object Detection (F32)
|
100% |
3338
249.2 IPS |
|
|
Object Detection (F16)
|
100% |
3711
277.0 IPS |
|
|
Object Detection (I8)
|
97% |
3594
268.3 IPS |
|
|
Face Detection (F32)
|
100% |
18490
219.9 IPS |
|
|
Face Detection (F16)
|
97% |
10753
127.9 IPS |
|
|
Face Detection (I8)
|
96% |
11222
133.4 IPS |
|
|
Depth Estimation (F32)
|
100% |
26902
208.6 IPS |
|
|
Depth Estimation (F16)
|
100% |
37182
288.3 IPS |
|
|
Depth Estimation (I8)
|
37% |
37896
293.9 IPS |
|
|
Style Transfer (F32)
|
100% |
102969
135.4 IPS |
|
|
Style Transfer (F16)
|
100% |
135768
178.6 IPS |
|
|
Style Transfer (I8)
|
100% |
132485
174.3 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
12968
463.1 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
16602
592.9 IPS |
|
|
Image Super-Resolution (I8)
|
100% |
18460
659.2 IPS |
|
|
Text Classification (F32)
|
100% |
621
891.8 IPS |
|
|
Text Classification (F16)
|
100% |
3142
4.52 KIPS |
|
|
Text Classification (I8)
|
96% |
2840
4.08 KIPS |
|
|
Machine Translation (F32)
|
100% |
963
17.7 IPS |
|
|
Machine Translation (F16)
|
100% |
1508
27.8 IPS |
|
|
Machine Translation (I8)
|
99% |
840
15.5 IPS |
