MacBook Pro (16-inch, Nov 2023)
Geekbench ML Score
9367
Core ML GPU Inference Score
Geekbench ML 0.6.0 for macOS AArch64
Result Information
| Upload Date | February 12 2024 06:24 PM |
| Views | 4 |
System Information
| System Information | |
|---|---|
| Operating System | macOS 14.2.1 (Build 23C71) |
| 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 | 4.01 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% |
5257
983.8 IPS |
|
|
Image Classification (F16)
|
100% |
6865
1.28 KIPS |
|
|
Image Classification (I8)
|
99% |
6250
1.17 KIPS |
|
|
Image Segmentation (F32)
|
100% |
2943
49.2 IPS |
|
|
Image Segmentation (F16)
|
100% |
2999
50.1 IPS |
|
|
Image Segmentation (I8)
|
100% |
2967
49.5 IPS |
|
|
Pose Estimation (F32)
|
100% |
84376
102.2 IPS |
|
|
Pose Estimation (F16)
|
100% |
59108
71.6 IPS |
|
|
Pose Estimation (I8)
|
100% |
82601
100.0 IPS |
|
|
Object Detection (F32)
|
100% |
3832
286.1 IPS |
|
|
Object Detection (F16)
|
100% |
5176
386.4 IPS |
|
|
Object Detection (I8)
|
97% |
3833
286.2 IPS |
|
|
Face Detection (F32)
|
100% |
23556
280.1 IPS |
|
|
Face Detection (F16)
|
97% |
24692
293.6 IPS |
|
|
Face Detection (I8)
|
96% |
21743
258.5 IPS |
|
|
Depth Estimation (F32)
|
100% |
26741
207.4 IPS |
|
|
Depth Estimation (F16)
|
100% |
37929
294.1 IPS |
|
|
Depth Estimation (I8)
|
37% |
36099
279.9 IPS |
|
|
Style Transfer (F32)
|
100% |
105562
138.9 IPS |
|
|
Style Transfer (F16)
|
100% |
139781
183.9 IPS |
|
|
Style Transfer (I8)
|
100% |
122002
160.5 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
15930
568.9 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
8343
297.9 IPS |
|
|
Image Super-Resolution (I8)
|
100% |
15513
554.0 IPS |
|
|
Text Classification (F32)
|
100% |
1413
2.03 KIPS |
|
|
Text Classification (F16)
|
100% |
985
1.42 KIPS |
|
|
Text Classification (I8)
|
96% |
641
921.5 IPS |
|
|
Machine Translation (F32)
|
100% |
809
14.9 IPS |
|
|
Machine Translation (F16)
|
100% |
805
14.8 IPS |
|
|
Machine Translation (I8)
|
99% |
763
14.0 IPS |
