MacBook Pro (16-inch, Nov 2023)
Geekbench ML Score
11980
Core ML GPU Inference Score
Geekbench ML 0.6.0 for macOS AArch64
Result Information
| Upload Date | September 10 2024 02:24 PM |
| Views | 3 |
System Information
| System Information | |
|---|---|
| Operating System | macOS 15.0 (Build 24A5320a) |
| 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 | 48.00 GB |
| Inference Information | |
|---|---|
| Framework | Core ML |
| Backend | GPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
6363
1.19 KIPS |
|
|
Image Classification (F16)
|
100% |
6427
1.20 KIPS |
|
|
Image Classification (I8)
|
99% |
6127
1.15 KIPS |
|
|
Image Segmentation (F32)
|
100% |
3137
52.4 IPS |
|
|
Image Segmentation (F16)
|
100% |
3177
53.1 IPS |
|
|
Image Segmentation (I8)
|
100% |
3064
51.2 IPS |
|
|
Pose Estimation (F32)
|
100% |
83452
101.1 IPS |
|
|
Pose Estimation (F16)
|
100% |
85620
103.7 IPS |
|
|
Pose Estimation (I8)
|
100% |
82698
100.1 IPS |
|
|
Object Detection (F32)
|
100% |
4363
325.8 IPS |
|
|
Object Detection (F16)
|
100% |
5193
387.7 IPS |
|
|
Object Detection (I8)
|
97% |
3685
275.1 IPS |
|
|
Face Detection (F32)
|
100% |
22129
263.1 IPS |
|
|
Face Detection (F16)
|
98% |
24563
292.1 IPS |
|
|
Face Detection (I8)
|
97% |
22181
263.7 IPS |
|
|
Depth Estimation (F32)
|
100% |
34577
268.1 IPS |
|
|
Depth Estimation (F16)
|
100% |
36877
286.0 IPS |
|
|
Depth Estimation (I8)
|
99% |
35534
275.6 IPS |
|
|
Style Transfer (F32)
|
100% |
160319
210.9 IPS |
|
|
Style Transfer (F16)
|
100% |
158301
208.2 IPS |
|
|
Style Transfer (I8)
|
100% |
161079
211.9 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
15478
552.8 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
16306
582.3 IPS |
|
|
Image Super-Resolution (I8)
|
100% |
14420
515.0 IPS |
|
|
Text Classification (F32)
|
100% |
2445
3.51 KIPS |
|
|
Text Classification (F16)
|
100% |
4217
6.06 KIPS |
|
|
Text Classification (I8)
|
96% |
4177
6.00 KIPS |
|
|
Machine Translation (F32)
|
100% |
1237
22.8 IPS |
|
|
Machine Translation (F16)
|
100% |
1236
22.7 IPS |
|
|
Machine Translation (I8)
|
99% |
1119
20.6 IPS |
