MacBook Pro (16-inch, Nov 2023)
Geekbench ML Score
10416
Core ML GPU Inference Score
Geekbench ML 0.6.0 for macOS AArch64
Result Information
| Upload Date | August 15 2024 05:13 PM |
| Views | 3 |
System Information
| System Information | |
|---|---|
| Operating System | macOS 14.6 (Build 23G80) |
| Model | MacBook Pro (16-inch, Nov 2023) |
| Model ID | Mac15,9 |
| Motherboard | Mac15,9 |
| CPU Information | |
|---|---|
| Name | Apple M3 Max |
| Topology | 1 Processor, 16 Cores |
| Identifier | Apple M3 Max |
| Base Frequency | 4.05 GHz |
| Cluster 1 | 12 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 | 128.00 GB |
| Inference Information | |
|---|---|
| Framework | Core ML |
| Backend | GPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
6941
1.30 KIPS |
|
|
Image Classification (F16)
|
100% |
7233
1.35 KIPS |
|
|
Image Classification (I8)
|
99% |
6697
1.25 KIPS |
|
|
Image Segmentation (F32)
|
100% |
2981
49.8 IPS |
|
|
Image Segmentation (F16)
|
100% |
3080
51.4 IPS |
|
|
Image Segmentation (I8)
|
100% |
2976
49.7 IPS |
|
|
Pose Estimation (F32)
|
100% |
84341
102.1 IPS |
|
|
Pose Estimation (F16)
|
100% |
88237
106.9 IPS |
|
|
Pose Estimation (I8)
|
100% |
84378
102.2 IPS |
|
|
Object Detection (F32)
|
100% |
4446
332.0 IPS |
|
|
Object Detection (F16)
|
100% |
5420
404.6 IPS |
|
|
Object Detection (I8)
|
97% |
4868
363.4 IPS |
|
|
Face Detection (F32)
|
100% |
24998
297.2 IPS |
|
|
Face Detection (F16)
|
98% |
27251
324.0 IPS |
|
|
Face Detection (I8)
|
97% |
24617
292.7 IPS |
|
|
Depth Estimation (F32)
|
100% |
35629
276.3 IPS |
|
|
Depth Estimation (F16)
|
100% |
38364
297.5 IPS |
|
|
Depth Estimation (I8)
|
37% |
37062
287.4 IPS |
|
|
Style Transfer (F32)
|
100% |
160179
210.7 IPS |
|
|
Style Transfer (F16)
|
100% |
173593
228.3 IPS |
|
|
Style Transfer (I8)
|
100% |
169989
223.6 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
16318
582.8 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
10102
360.8 IPS |
|
|
Image Super-Resolution (I8)
|
100% |
14955
534.1 IPS |
|
|
Text Classification (F32)
|
100% |
542
779.2 IPS |
|
|
Text Classification (F16)
|
100% |
842
1.21 KIPS |
|
|
Text Classification (I8)
|
96% |
842
1.21 KIPS |
|
|
Machine Translation (F32)
|
100% |
1121
20.6 IPS |
|
|
Machine Translation (F16)
|
100% |
1124
20.7 IPS |
|
|
Machine Translation (I8)
|
99% |
1050
19.3 IPS |
