Mac Studio (2023)
Geekbench ML Score
3523
Core ML CPU Inference Score
Geekbench ML 0.6.0 for macOS AArch64
Result Information
| Upload Date | August 15 2024 06:09 PM |
| Views | 2 |
System Information
| System Information | |
|---|---|
| Operating System | macOS 14.5 (Build 23F79) |
| Model | Mac Studio (2023) |
| Model ID | Mac14,13 |
| Motherboard | Mac14,13 |
| CPU Information | |
|---|---|
| Name | Apple M2 Max |
| Topology | 1 Processor, 12 Cores |
| Identifier | Apple M2 Max |
| Base Frequency | 3.66 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 | CPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
1463
273.7 IPS |
|
|
Image Classification (F16)
|
100% |
1823
341.1 IPS |
|
|
Image Classification (I8)
|
99% |
1835
343.5 IPS |
|
|
Image Segmentation (F32)
|
100% |
903
15.1 IPS |
|
|
Image Segmentation (F16)
|
100% |
910
15.2 IPS |
|
|
Image Segmentation (I8)
|
100% |
909
15.2 IPS |
|
|
Pose Estimation (F32)
|
100% |
6082
7.36 IPS |
|
|
Pose Estimation (F16)
|
100% |
14343
17.4 IPS |
|
|
Pose Estimation (I8)
|
100% |
14383
17.4 IPS |
|
|
Object Detection (F32)
|
100% |
1479
110.4 IPS |
|
|
Object Detection (F16)
|
100% |
1989
148.5 IPS |
|
|
Object Detection (I8)
|
97% |
1488
111.1 IPS |
|
|
Face Detection (F32)
|
100% |
3025
36.0 IPS |
|
|
Face Detection (F16)
|
97% |
4382
52.1 IPS |
|
|
Face Detection (I8)
|
97% |
4392
52.2 IPS |
|
|
Depth Estimation (F32)
|
100% |
5537
42.9 IPS |
|
|
Depth Estimation (F16)
|
100% |
8599
66.7 IPS |
|
|
Depth Estimation (I8)
|
99% |
8618
66.8 IPS |
|
|
Style Transfer (F32)
|
100% |
16823
22.1 IPS |
|
|
Style Transfer (F16)
|
100% |
26397
34.7 IPS |
|
|
Style Transfer (I8)
|
100% |
26218
34.5 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
3942
140.8 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
5113
182.6 IPS |
|
|
Image Super-Resolution (I8)
|
100% |
5002
178.6 IPS |
|
|
Text Classification (F32)
|
100% |
2118
3.04 KIPS |
|
|
Text Classification (F16)
|
100% |
3170
4.56 KIPS |
|
|
Text Classification (I8)
|
96% |
3259
4.68 KIPS |
|
|
Machine Translation (F32)
|
100% |
1139
21.0 IPS |
|
|
Machine Translation (F16)
|
100% |
1576
29.0 IPS |
|
|
Machine Translation (I8)
|
99% |
1156
21.3 IPS |
