MacBook Pro (16-inch, 2023)
Geekbench ML Score
9465
Core ML Neural Engine Inference Score
Geekbench ML 0.6.0 for macOS AArch64
Result Information
| Upload Date | May 08 2024 03:00 PM |
| Views | 3 |
System Information
| System Information | |
|---|---|
| Operating System | macOS 14.4.1 (Build 23E224) |
| Model | MacBook Pro (16-inch, 2023) |
| Model ID | Mac14,6 |
| Motherboard | Mac14,6 |
| CPU Information | |
|---|---|
| Name | Apple M2 Max |
| Topology | 1 Processor, 12 Cores |
| Identifier | Apple M2 Max |
| Base Frequency | 3.58 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 | 96.00 GB |
| Inference Information | |
|---|---|
| Framework | Core ML |
| Backend | Neural Engine |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
5867
1.10 KIPS |
|
|
Image Classification (F16)
|
100% |
7443
1.39 KIPS |
|
|
Image Classification (I8)
|
99% |
8398
1.57 KIPS |
|
|
Image Segmentation (F32)
|
100% |
2253
37.6 IPS |
|
|
Image Segmentation (F16)
|
100% |
1900
31.7 IPS |
|
|
Image Segmentation (I8)
|
100% |
1859
31.1 IPS |
|
|
Pose Estimation (F32)
|
100% |
53103
64.3 IPS |
|
|
Pose Estimation (F16)
|
100% |
80539
97.5 IPS |
|
|
Pose Estimation (I8)
|
100% |
83171
100.7 IPS |
|
|
Object Detection (F32)
|
100% |
3801
283.8 IPS |
|
|
Object Detection (F16)
|
100% |
3921
292.7 IPS |
|
|
Object Detection (I8)
|
97% |
3691
275.6 IPS |
|
|
Face Detection (F32)
|
100% |
19769
235.1 IPS |
|
|
Face Detection (F16)
|
97% |
10716
127.4 IPS |
|
|
Face Detection (I8)
|
96% |
11344
134.9 IPS |
|
|
Depth Estimation (F32)
|
100% |
30954
240.1 IPS |
|
|
Depth Estimation (F16)
|
100% |
28376
220.1 IPS |
|
|
Depth Estimation (I8)
|
37% |
33888
262.8 IPS |
|
|
Style Transfer (F32)
|
100% |
121101
159.3 IPS |
|
|
Style Transfer (F16)
|
100% |
133570
175.7 IPS |
|
|
Style Transfer (I8)
|
100% |
135366
178.1 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
11823
422.2 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
18515
661.2 IPS |
|
|
Image Super-Resolution (I8)
|
100% |
17313
618.3 IPS |
|
|
Text Classification (F32)
|
100% |
936
1.35 KIPS |
|
|
Text Classification (F16)
|
100% |
2811
4.04 KIPS |
|
|
Text Classification (I8)
|
96% |
2785
4.00 KIPS |
|
|
Machine Translation (F32)
|
100% |
723
13.3 IPS |
|
|
Machine Translation (F16)
|
100% |
1495
27.5 IPS |
|
|
Machine Translation (I8)
|
99% |
717
13.2 IPS |
