MacBook Pro (16-inch, Nov 2023)
Geekbench ML Score
10501
Core ML GPU Inference Score
Geekbench ML 0.6.0 for macOS AArch64
Result Information
| Upload Date | May 09 2024 09:43 AM |
| Views | 3 |
System Information
| System Information | |
|---|---|
| Operating System | macOS 14.5 (Build 23F5074a) |
| 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% |
6936
1.30 KIPS |
|
|
Image Classification (F16)
|
100% |
7113
1.33 KIPS |
|
|
Image Classification (I8)
|
99% |
6738
1.26 KIPS |
|
|
Image Segmentation (F32)
|
100% |
3160
52.8 IPS |
|
|
Image Segmentation (F16)
|
100% |
3171
53.0 IPS |
|
|
Image Segmentation (I8)
|
100% |
3309
55.3 IPS |
|
|
Pose Estimation (F32)
|
100% |
84064
101.8 IPS |
|
|
Pose Estimation (F16)
|
100% |
88578
107.3 IPS |
|
|
Pose Estimation (I8)
|
100% |
84735
102.6 IPS |
|
|
Object Detection (F32)
|
100% |
3700
276.2 IPS |
|
|
Object Detection (F16)
|
100% |
5470
408.3 IPS |
|
|
Object Detection (I8)
|
97% |
3986
297.5 IPS |
|
|
Face Detection (F32)
|
100% |
26826
319.0 IPS |
|
|
Face Detection (F16)
|
98% |
29895
355.5 IPS |
|
|
Face Detection (I8)
|
97% |
27648
328.7 IPS |
|
|
Depth Estimation (F32)
|
100% |
35751
277.2 IPS |
|
|
Depth Estimation (F16)
|
100% |
38150
295.9 IPS |
|
|
Depth Estimation (I8)
|
37% |
37318
289.4 IPS |
|
|
Style Transfer (F32)
|
100% |
157484
207.2 IPS |
|
|
Style Transfer (F16)
|
100% |
164623
216.5 IPS |
|
|
Style Transfer (I8)
|
100% |
161726
212.7 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
16153
576.9 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
10122
361.5 IPS |
|
|
Image Super-Resolution (I8)
|
100% |
9714
346.9 IPS |
|
|
Text Classification (F32)
|
100% |
1136
1.63 KIPS |
|
|
Text Classification (F16)
|
100% |
866
1.24 KIPS |
|
|
Text Classification (I8)
|
96% |
879
1.26 KIPS |
|
|
Machine Translation (F32)
|
100% |
1108
20.4 IPS |
|
|
Machine Translation (F16)
|
100% |
1114
20.5 IPS |
|
|
Machine Translation (I8)
|
99% |
964
17.7 IPS |
